Results for “MINIMIZATION” — Page 96

DOE OSTI2016

On post-inflation validity of perturbation theory in Horndeski scalar-tensor models

By using the newtonian gauge, we re-confirm that, as in the minimal case, the re-scaled Mukhanov-Sasaki variable is conserved leading to a constraint equation for the Newtonian potential. However, conversely to the minimal case, in Horndeski theories, the super-horizon Newtonian potential can potentially grow to very large values after inflation exit. If that happens, inflationary predictability is lost during the oscillating period. When this does not happen, the perturbations generated during inflation can be standardly related to the CMB, if the theory chosen is minimal at low energies. As a concrete example, we analytically and numerically discuss the new Higgs inflationary case. There, the Inflaton is the Higgs boson that is non-minimally kinetically coupled to gravity. During the high-energy part of the post-inflationary oscillations, the system is anisotropic and the Newtonian potential is largely amplified. Thanks to the smallness of today's amplitude of curvature perturbations, however, the system stays in the linear regime, so that inflationary predictions are not lost. At low energies, when the system relaxes to the minimal case, the anisotropies disappear and the Newtonian potential converges to a constant value. We show that the constant value to which the Newtonian potential converges is related to the frozen part of curvature perturbations during inflation, precisely like in the minimal case.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Nodal variational principle for excited states

It is proven that the exact excited-state wave function and energy may be obtained by minimizing the energy expectation value of trial wave functions that are constrained only to have the correct nodes of the state of interest. This excited-state nodal minimum principle has the advantage that it requires neither minimization with the constraint of wave-function orthogonality to all lower eigenstates nor the antisymmetry of the trial wave functions. It is also found that the minimization over the entire space can be partitioned into several interconnected minimizations within the individual nodal regions, and the exact excited-state energy may be obtained by a minimization in just one or several of these nodal regions. For the proofs of the theorem, it is observed that the many-electron eigenfunction (excited state as well as ground state), restricted to a nodal region, is equivalent to a ground-state wave function of one electron in a higher-dimensional space; and, alternatively, an explicit excited-state energy variational expression is utilized by generalizing the Jacobi method of multiplicative variation. In corollaries, error functions are constructed for cases for which the nodes are not necessarily exact. The exact nodes minimize the energy error functions with respect to nodal variations. In conclusion, simple numerical illustrations of the error functions are presented.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2014

SU-E-T-592: Relationship Between Dose of Distribution and Area of Segment Fields Among Different Intensity-Modulated Radiotherapy Planning in Cervix Cancer

Purpose: In premise of uninfluenced to dose distribution of tumor target and organ at risk(OAR) in cervical cancer,area of segment fields was changed to increase efficacy and optimize treatment method by designing different plan of intensity modulated radiotherapy(IMRT). Methods: 12 cases of cervical cancer were confirmed in pathology and treated with step and shoot IMRT. Dose of PTV was 50Gy/25fractions. Every patient was designed 9 treatment plans of IMRT by Pinnacle 8.0m planning system,each plan was used with 9 beams of uniform distribution and fixing incidence direction(200°,240°,280°,320°,0°,40°,80°,120°and 160°respectively),and designed for delivery on Elekta Synergy linear accelerator. All plans were optimized with the direct machine parameter optimization(DMPO) algorithm using the same set of optimization objectives. Number of maximum segment field was defined at 80 and minimum MU in each segment was 5MU,and minimal segment area was 2*1cm{sup 2},2*2cm{sup 2},3*3cm{sup 2},4*4cm{sup 2},5*5cm{sup 2},6*6cm{sup 2},7*7cm{sup 2},8*8cm{sup 2}and 9*9cm{sup 2},respectively.Coverage,homogeneity and conformity of PTV,sparing of OAR, MU and number of segment were compared. Results: In this group, mean volume of PTV was 916.8±228.7 cm{sup 3}. Compared with the area of minimal segment field increased from 2*1cm{sup 2} to 9*9 cm{sup 2},the number of mean MU was decreased from 1405±170 to 490±47 and the number of segment field was reduced from 76±4 to 39±7 respectively(p<0.05). When the limit of minimal segment area was increased from 2*1cm{sup 2} to 7*7 cm{sup 2},dose distribution of PTV,OAR,CI,HI and V{sub 2} {sub 3} were not different (p>0.05),but when the minimal segment area was 8*8 cm{sup 2} and 9*9 cm{sup 2},they were changed compared with 7*7 cm{sup 2} and below(p<0.05). Conclusion: The minimal segment field of IMRT plan designed by Pinnacle 8.0m planning system in cervical carcinoma should be enlarge reasonably and minimal segment area of 7*7 cm{sup 2} was recommend.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-207A-00: Advances in Image-Guided Neurointerventions-Clinical Pull and Technology Push

1. Parallels in the evolution of x-ray angiographic systems and devices used for minimally invasive endovascular therapy Charles Strother - DSA, invented by Dr. Charles Mistretta at UW-Madison, was the technology which enabled the development of minimally invasive endovascular procedures. As DSA became widely available and the potential benefits for accessing the cerebral vasculature from an endovascular approach began to be apparent, industry began efforts to develop tools for use in these procedures. Along with development of catheters, embolic materials, pushable coils and the GDC coils there was simultaneous development and improvement of 2D DSA image quality and the introduction of 3D DSA. Together, these advances resulted in an enormous expansion in the scope and numbers of minimally invasive endovascular procedures. The introduction of flat detectors for c-arm angiographic systems in 2002 provided the possibility of the angiographic suite becoming not just a location for vascular imaging where physiological assessments might also be performed. Over the last decade algorithmic and hardware advances have been sufficient to now realize this potential in clinical practice. The selection of patients for endovascular treatments is enhanced by this dual capability. Along with these advances has been a steady reduction in the radiation exposure required so that today, vascular and soft tissue images may be obtained with equal or in many cases less radiation exposure than is the case for comparable images obtained with multi-detector CT. Learning Objectives: To understand the full capabilities of today’s angiographic suite To understand how c-arm cone beam CT soft tissue imaging can be used for assessments of devices, blood flow and perfusion. Advances in real-time x-ray neuro-endovascular image guidance Stephen Rudin - Reacting to the demands on real-time image guidance for ever finer neurovascular interventions, great improvements in imaging chains are being pursued. For the highest spatial and temporal resolution, x-ray guidance with fluoroscopy and angiography although dominant are still being vastly improved. New detectors such as the Micro-Angiographic Fluoroscope (MAF) and x-ray source designs that enable higher outputs while maintaining small focal spots will be highlighted along with new methods for minimizing the radiation dose to patients. Additionally, new platforms for training and device testing that include patient-specific 3D printed vascular phantoms and new metrics such as generalized relative object detectability for objectively inter-comparing systems will be discussed. This will improve the opportunity for better evaluation of these technological advances which should contribute to the safety and efficacy of image guided minimally invasive neuro-endovascular procedures. Learning Objectives: To understand the operation of new x-ray imaging chain components such as detectors and sources To be informed about the latest testing methods, with 3D printed vascular phantoms, and new evaluation metrics for advanced imaging in x-ray image guided neurovascular interventions Advances in cone beam CT anatomical and functional imaging in angio-suite to enable one-stop-shop stroke imaging workflow Guang-Hong Chen - The introduction of flat-panel detector based cone-beam CT in clinical angiographic imaging systems enabled treating physicians to obtain three-dimensional anatomic roadmaps for bony structure, soft brain tissue, and vasculatures for treatment planning and efficacy checking after the procedures. However, much improvement is needed to reduce image artifacts, reduce radiation dose, and add potential functional imaging capability to provide four-dimensional dynamic information of vasculature and brain perfusion. In this presentation, some of the new techniques developed to address radiation dose issues, image artifact reduction and brain perfusion using C-arm cone-beam CT imaging system will be introduced for the audience. Learning Objectives: To understand the clinical need of one-stop-shop stroke imaging workflow To understand to technical challenges in cone beam CT perfusion To understand the potential technical solutions to enable one-stop-shop imaging workflow Recent advances in devices used in neuro--interventions Mattew Gounis - Over the past two decades, there has been explosive development of medical devices that have revolutionized the endovascular treatment of cerebrovascular diseases. There is now Level 1, Class A evidence that intra-arterial, mechanical thrombectomy in acute ischemic stroke is superior to medical management; and similarly that minimally invasive, endovascular repair of ruptured brain aneurysms is superior to surgical treatment. Stent-retrievers are now standard of care for emergent large vessel occlusions causing a stroke, with a number of patients need to treat for good clinical outcomes as low as 4. Recent technologies such as flow diverters and disrupters, intracranial self-expanding stents, flexible large bore catheters that can reach vessels beyond the circle of Willis, stent-retrievers, and super-compliant balloons are the result of successful miniaturization of design features and novel manufacturing technologies capable of building these devices. This is a rapidly evolving field, and the device technology enabling such advancements will be reviewed. Importantly, image-guidance technology has not kept pace in neurointervention and the ability to adequately characterize these devices in vivo remains a significant opportunity. Learning Objectives: A survey of devices used in neurointerventions, their materials and essential design characteristics Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; G. Chen, Funding received from NIH; funding received from DOD; funding received from GE Healthcare; funding received from Siemens AX.; M. Gounis, consultant for Codman Neurovascular and Stryker Neurovascular; Holds stock in InNeuroCo Inc, research grants: NIH, Medtronic Neurovascular, Microvention/Terumo, Cerevasc LLC, Gentuity, Codman Neurovascular, Philips Healthcare, Stryker Neurovascular, Tay Sachs Foundation, and InNeuroCo Inc.; S. Rudin, Supported in part by NIH Grant R01EB002873 and the Toshiba Medical System Corp.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-207A-02: Advances in Cone Beam CT Anatomical and Functional Imaging in Angio-Suite to Enable One-Stop-Shop Stroke Imaging Workflow

1. Parallels in the evolution of x-ray angiographic systems and devices used for minimally invasive endovascular therapy Charles Strother - DSA, invented by Dr. Charles Mistretta at UW-Madison, was the technology which enabled the development of minimally invasive endovascular procedures. As DSA became widely available and the potential benefits for accessing the cerebral vasculature from an endovascular approach began to be apparent, industry began efforts to develop tools for use in these procedures. Along with development of catheters, embolic materials, pushable coils and the GDC coils there was simultaneous development and improvement of 2D DSA image quality and the introduction of 3D DSA. Together, these advances resulted in an enormous expansion in the scope and numbers of minimally invasive endovascular procedures. The introduction of flat detectors for c-arm angiographic systems in 2002 provided the possibility of the angiographic suite becoming not just a location for vascular imaging where physiological assessments might also be performed. Over the last decade algorithmic and hardware advances have been sufficient to now realize this potential in clinical practice. The selection of patients for endovascular treatments is enhanced by this dual capability. Along with these advances has been a steady reduction in the radiation exposure required so that today, vascular and soft tissue images may be obtained with equal or in many cases less radiation exposure than is the case for comparable images obtained with multi-detector CT. Learning Objectives: To understand the full capabilities of today’s angiographic suite To understand how c-arm cone beam CT soft tissue imaging can be used for assessments of devices, blood flow and perfusion. Advances in real-time x-ray neuro-endovascular image guidance Stephen Rudin - Reacting to the demands on real-time image guidance for ever finer neurovascular interventions, great improvements in imaging chains are being pursued. For the highest spatial and temporal resolution, x-ray guidance with fluoroscopy and angiography although dominant are still being vastly improved. New detectors such as the Micro-Angiographic Fluoroscope (MAF) and x-ray source designs that enable higher outputs while maintaining small focal spots will be highlighted along with new methods for minimizing the radiation dose to patients. Additionally, new platforms for training and device testing that include patient-specific 3D printed vascular phantoms and new metrics such as generalized relative object detectability for objectively inter-comparing systems will be discussed. This will improve the opportunity for better evaluation of these technological advances which should contribute to the safety and efficacy of image guided minimally invasive neuro-endovascular procedures. Learning Objectives: To understand the operation of new x-ray imaging chain components such as detectors and sources To be informed about the latest testing methods, with 3D printed vascular phantoms, and new evaluation metrics for advanced imaging in x-ray image guided neurovascular interventions Advances in cone beam CT anatomical and functional imaging in angio-suite to enable one-stop-shop stroke imaging workflow Guang-Hong Chen - The introduction of flat-panel detector based cone-beam CT in clinical angiographic imaging systems enabled treating physicians to obtain three-dimensional anatomic roadmaps for bony structure, soft brain tissue, and vasculatures for treatment planning and efficacy checking after the procedures. However, much improvement is needed to reduce image artifacts, reduce radiation dose, and add potential functional imaging capability to provide four-dimensional dynamic information of vasculature and brain perfusion. In this presentation, some of the new techniques developed to address radiation dose issues, image artifact reduction and brain perfusion using C-arm cone-beam CT imaging system will be introduced for the audience. Learning Objectives: To understand the clinical need of one-stop-shop stroke imaging workflow To understand to technical challenges in cone beam CT perfusion To understand the potential technical solutions to enable one-stop-shop imaging workflow Recent advances in devices used in neuro--interventions Mattew Gounis - Over the past two decades, there has been explosive development of medical devices that have revolutionized the endovascular treatment of cerebrovascular diseases. There is now Level 1, Class A evidence that intra-arterial, mechanical thrombectomy in acute ischemic stroke is superior to medical management; and similarly that minimally invasive, endovascular repair of ruptured brain aneurysms is superior to surgical treatment. Stent-retrievers are now standard of care for emergent large vessel occlusions causing a stroke, with a number of patients need to treat for good clinical outcomes as low as 4. Recent technologies such as flow diverters and disrupters, intracranial self-expanding stents, flexible large bore catheters that can reach vessels beyond the circle of Willis, stent-retrievers, and super-compliant balloons are the result of successful miniaturization of design features and novel manufacturing technologies capable of building these devices. This is a rapidly evolving field, and the device technology enabling such advancements will be reviewed. Importantly, image-guidance technology has not kept pace in neurointervention and the ability to adequately characterize these devices in vivo remains a significant opportunity. Learning Objectives: A survey of devices used in neurointerventions, their materials and essential design characteristics Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; G. Chen, Funding received from NIH; funding received from DOD; funding received from GE Healthcare; funding received from Siemens AX.; M. Gounis, consultant for Codman Neurovascular and Stryker Neurovascular; Holds stock in InNeuroCo Inc, research grants: NIH, Medtronic Neurovascular, Microvention/Terumo, Cerevasc LLC, Gentuity, Codman Neurovascular, Philips Healthcare, Stryker Neurovascular, Tay Sachs Foundation, and InNeuroCo Inc.; S. Rudin, Supported in part by NIH Grant R01EB002873 and the Toshiba Medical System Corp.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-207A-03: Recent Advances in Devices Used in Neuro--Interventions

1. Parallels in the evolution of x-ray angiographic systems and devices used for minimally invasive endovascular therapy Charles Strother - DSA, invented by Dr. Charles Mistretta at UW-Madison, was the technology which enabled the development of minimally invasive endovascular procedures. As DSA became widely available and the potential benefits for accessing the cerebral vasculature from an endovascular approach began to be apparent, industry began efforts to develop tools for use in these procedures. Along with development of catheters, embolic materials, pushable coils and the GDC coils there was simultaneous development and improvement of 2D DSA image quality and the introduction of 3D DSA. Together, these advances resulted in an enormous expansion in the scope and numbers of minimally invasive endovascular procedures. The introduction of flat detectors for c-arm angiographic systems in 2002 provided the possibility of the angiographic suite becoming not just a location for vascular imaging where physiological assessments might also be performed. Over the last decade algorithmic and hardware advances have been sufficient to now realize this potential in clinical practice. The selection of patients for endovascular treatments is enhanced by this dual capability. Along with these advances has been a steady reduction in the radiation exposure required so that today, vascular and soft tissue images may be obtained with equal or in many cases less radiation exposure than is the case for comparable images obtained with multi-detector CT. Learning Objectives: To understand the full capabilities of today’s angiographic suite To understand how c-arm cone beam CT soft tissue imaging can be used for assessments of devices, blood flow and perfusion. Advances in real-time x-ray neuro-endovascular image guidance Stephen Rudin - Reacting to the demands on real-time image guidance for ever finer neurovascular interventions, great improvements in imaging chains are being pursued. For the highest spatial and temporal resolution, x-ray guidance with fluoroscopy and angiography although dominant are still being vastly improved. New detectors such as the Micro-Angiographic Fluoroscope (MAF) and x-ray source designs that enable higher outputs while maintaining small focal spots will be highlighted along with new methods for minimizing the radiation dose to patients. Additionally, new platforms for training and device testing that include patient-specific 3D printed vascular phantoms and new metrics such as generalized relative object detectability for objectively inter-comparing systems will be discussed. This will improve the opportunity for better evaluation of these technological advances which should contribute to the safety and efficacy of image guided minimally invasive neuro-endovascular procedures. Learning Objectives: To understand the operation of new x-ray imaging chain components such as detectors and sources To be informed about the latest testing methods, with 3D printed vascular phantoms, and new evaluation metrics for advanced imaging in x-ray image guided neurovascular interventions Advances in cone beam CT anatomical and functional imaging in angio-suite to enable one-stop-shop stroke imaging workflow Guang-Hong Chen - The introduction of flat-panel detector based cone-beam CT in clinical angiographic imaging systems enabled treating physicians to obtain three-dimensional anatomic roadmaps for bony structure, soft brain tissue, and vasculatures for treatment planning and efficacy checking after the procedures. However, much improvement is needed to reduce image artifacts, reduce radiation dose, and add potential functional imaging capability to provide four-dimensional dynamic information of vasculature and brain perfusion. In this presentation, some of the new techniques developed to address radiation dose issues, image artifact reduction and brain perfusion using C-arm cone-beam CT imaging system will be introduced for the audience. Learning Objectives: To understand the clinical need of one-stop-shop stroke imaging workflow To understand to technical challenges in cone beam CT perfusion To understand the potential technical solutions to enable one-stop-shop imaging workflow Recent advances in devices used in neuro--interventions Mattew Gounis - Over the past two decades, there has been explosive development of medical devices that have revolutionized the endovascular treatment of cerebrovascular diseases. There is now Level 1, Class A evidence that intra-arterial, mechanical thrombectomy in acute ischemic stroke is superior to medical management; and similarly that minimally invasive, endovascular repair of ruptured brain aneurysms is superior to surgical treatment. Stent-retrievers are now standard of care for emergent large vessel occlusions causing a stroke, with a number of patients need to treat for good clinical outcomes as low as 4. Recent technologies such as flow diverters and disrupters, intracranial self-expanding stents, flexible large bore catheters that can reach vessels beyond the circle of Willis, stent-retrievers, and super-compliant balloons are the result of successful miniaturization of design features and novel manufacturing technologies capable of building these devices. This is a rapidly evolving field, and the device technology enabling such advancements will be reviewed. Importantly, image-guidance technology has not kept pace in neurointervention and the ability to adequately characterize these devices in vivo remains a significant opportunity. Learning Objectives: A survey of devices used in neurointerventions, their materials and essential design characteristics Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; G. Chen, Funding received from NIH; funding received from DOD; funding received from GE Healthcare; funding received from Siemens AX.; M. Gounis, consultant for Codman Neurovascular and Stryker Neurovascular; Holds stock in InNeuroCo Inc, research grants: NIH, Medtronic Neurovascular, Microvention/Terumo, Cerevasc LLC, Gentuity, Codman Neurovascular, Philips Healthcare, Stryker Neurovascular, Tay Sachs Foundation, and InNeuroCo Inc.; S. Rudin, Supported in part by NIH Grant R01EB002873 and the Toshiba Medical System Corp.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-207A-04: Advances in Radiological Neuro-Endovascular Interventional Imaging

1. Parallels in the evolution of x-ray angiographic systems and devices used for minimally invasive endovascular therapy Charles Strother - DSA, invented by Dr. Charles Mistretta at UW-Madison, was the technology which enabled the development of minimally invasive endovascular procedures. As DSA became widely available and the potential benefits for accessing the cerebral vasculature from an endovascular approach began to be apparent, industry began efforts to develop tools for use in these procedures. Along with development of catheters, embolic materials, pushable coils and the GDC coils there was simultaneous development and improvement of 2D DSA image quality and the introduction of 3D DSA. Together, these advances resulted in an enormous expansion in the scope and numbers of minimally invasive endovascular procedures. The introduction of flat detectors for c-arm angiographic systems in 2002 provided the possibility of the angiographic suite becoming not just a location for vascular imaging where physiological assessments might also be performed. Over the last decade algorithmic and hardware advances have been sufficient to now realize this potential in clinical practice. The selection of patients for endovascular treatments is enhanced by this dual capability. Along with these advances has been a steady reduction in the radiation exposure required so that today, vascular and soft tissue images may be obtained with equal or in many cases less radiation exposure than is the case for comparable images obtained with multi-detector CT. Learning Objectives: To understand the full capabilities of today’s angiographic suite To understand how c-arm cone beam CT soft tissue imaging can be used for assessments of devices, blood flow and perfusion. Advances in real-time x-ray neuro-endovascular image guidance Stephen Rudin - Reacting to the demands on real-time image guidance for ever finer neurovascular interventions, great improvements in imaging chains are being pursued. For the highest spatial and temporal resolution, x-ray guidance with fluoroscopy and angiography although dominant are still being vastly improved. New detectors such as the Micro-Angiographic Fluoroscope (MAF) and x-ray source designs that enable higher outputs while maintaining small focal spots will be highlighted along with new methods for minimizing the radiation dose to patients. Additionally, new platforms for training and device testing that include patient-specific 3D printed vascular phantoms and new metrics such as generalized relative object detectability for objectively inter-comparing systems will be discussed. This will improve the opportunity for better evaluation of these technological advances which should contribute to the safety and efficacy of image guided minimally invasive neuro-endovascular procedures. Learning Objectives: To understand the operation of new x-ray imaging chain components such as detectors and sources To be informed about the latest testing methods, with 3D printed vascular phantoms, and new evaluation metrics for advanced imaging in x-ray image guided neurovascular interventions Advances in cone beam CT anatomical and functional imaging in angio-suite to enable one-stop-shop stroke imaging workflow Guang-Hong Chen - The introduction of flat-panel detector based cone-beam CT in clinical angiographic imaging systems enabled treating physicians to obtain three-dimensional anatomic roadmaps for bony structure, soft brain tissue, and vasculatures for treatment planning and efficacy checking after the procedures. However, much improvement is needed to reduce image artifacts, reduce radiation dose, and add potential functional imaging capability to provide four-dimensional dynamic information of vasculature and brain perfusion. In this presentation, some of the new techniques developed to address radiation dose issues, image artifact reduction and brain perfusion using C-arm cone-beam CT imaging system will be introduced for the audience. Learning Objectives: To understand the clinical need of one-stop-shop stroke imaging workflow To understand to technical challenges in cone beam CT perfusion To understand the potential technical solutions to enable one-stop-shop imaging workflow Recent advances in devices used in neuro--interventions Mattew Gounis - Over the past two decades, there has been explosive development of medical devices that have revolutionized the endovascular treatment of cerebrovascular diseases. There is now Level 1, Class A evidence that intra-arterial, mechanical thrombectomy in acute ischemic stroke is superior to medical management; and similarly that minimally invasive, endovascular repair of ruptured brain aneurysms is superior to surgical treatment. Stent-retrievers are now standard of care for emergent large vessel occlusions causing a stroke, with a number of patients need to treat for good clinical outcomes as low as 4. Recent technologies such as flow diverters and disrupters, intracranial self-expanding stents, flexible large bore catheters that can reach vessels beyond the circle of Willis, stent-retrievers, and super-compliant balloons are the result of successful miniaturization of design features and novel manufacturing technologies capable of building these devices. This is a rapidly evolving field, and the device technology enabling such advancements will be reviewed. Importantly, image-guidance technology has not kept pace in neurointervention and the ability to adequately characterize these devices in vivo remains a significant opportunity. Learning Objectives: A survey of devices used in neurointerventions, their materials and essential design characteristics Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; G. Chen, Funding received from NIH; funding received from DOD; funding received from GE Healthcare; funding received from Siemens AX.; M. Gounis, consultant for Codman Neurovascular and Stryker Neurovascular; Holds stock in InNeuroCo Inc, research grants: NIH, Medtronic Neurovascular, Microvention/Terumo, Cerevasc LLC, Gentuity, Codman Neurovascular, Philips Healthcare, Stryker Neurovascular, Tay Sachs Foundation, and InNeuroCo Inc.; S. Rudin, Supported in part by NIH Grant R01EB002873 and the Toshiba Medical System Corp.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1995

The trellis complexity of convolutional codes

It has long been known that convolutional codes have a natural, regular trellis structure that facilitates the implementation of Viterbi's algorithm. It has gradually become apparent that linear block codes also have a natural, though not in general a regular, 'minimal' trellis structure, which allows them to be decoded with a Viterbi-like algorithm. In both cases, the complexity of the Viterbi decoding algorithm can be accurately estimated by the number of trellis edges per encoded bit. It would, therefore, appear that we are in a good position to make a fair comparison of the Viterbi decoding complexity of block and convolutional codes. Unfortunately, however, this comparison is somewhat muddled by the fact that some convolutional codes, the punctured convolutional codes, are known to have trellis representations that are significantly less complex than the conventional trellis. In other words, the conventional trellis representation for a convolutional code may not be the minimal trellis representation. Thus, ironically, at present we seem to know more about the minimal trellis representation for block than for convolutional codes. In this article, we provide a remedy, by developing a theory of minimal trellises for convolutional codes. (A similar theory has recently been given by Sidorenko and Zyablov). This allows us to make a direct performance-complexity comparison for block and convolutional codes. A by-product of our work is an algorithm for choosing, from among all generator matrices for a given convolutional code, what we call a trellis-minimal generator matrix, from which the minimal trellis for the code can be directly constructed. Another by-product is that, in the new theory, punctured convolutional codes no longer appear as a special class, but simply as high-rate convolutional codes whose trellis complexity is unexpectedly small.

Mceliece, R. J.↗

NASA NTRS1999

Optimized System Identification

In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

Juang, Jer-Nan↗

NASA NTRS2002

Quadratic Optimization in the Problems of Active Control of Sound

We analyze the problem of suppressing the unwanted component of a time-harmonic acoustic field (noise) on a predetermined region of interest. The suppression is rendered by active means, i.e., by introducing the additional acoustic sources called controls that generate the appropriate anti-sound. Previously, we have obtained general solutions for active controls in both continuous and discrete formulations of the problem. We have also obtained optimal solutions that minimize the overall absolute acoustic source strength of active control sources. These optimal solutions happen to be particular layers of monopoles on the perimeter of the protected region. Mathematically, minimization of acoustic source strength is equivalent to minimization in the sense of L(sub 1). By contrast. in the current paper we formulate and study optimization problems that involve quadratic functions of merit. Specifically, we minimize the L(sub 2) norm of the control sources, and we consider both the unconstrained and constrained minimization. The unconstrained L(sub 2) minimization is certainly the easiest problem to address numerically. On the other hand, the constrained approach allows one to analyze sophisticated geometries. In a special case, we call compare our finite-difference optimal solutions to the continuous optimal solutions obtained previously using a semi-analytic technique. We also show that the optima obtained in the sense of L(sub 2) differ drastically from those obtained in the sense of L(sub 1).

Loncaric, J.↗

NASA NTRS2005

Biased Randomized Algorithm for Fast Model-Based Diagnosis

A biased randomized algorithm has been developed to enable the rapid computational solution of a propositional- satisfiability (SAT) problem equivalent to a diagnosis problem. The closest competing methods of automated diagnosis are described in the preceding article "Fast Algorithms for Model-Based Diagnosis" and "Two Methods of Efficient Solution of the Hitting-Set Problem" (NPO-30584), which appears elsewhere in this issue. It is necessary to recapitulate some of the information from the cited articles as a prerequisite to a description of the present method. As used here, "diagnosis" signifies, more precisely, a type of model-based diagnosis in which one explores any logical inconsistencies between the observed and expected behaviors of an engineering system. The function of each component and the interconnections among all the components of the engineering system are represented as a logical system. Hence, the expected behavior of the engineering system is represented as a set of logical consequences. Faulty components lead to inconsistency between the observed and expected behaviors of the system, represented by logical inconsistencies. Diagnosis - the task of finding the faulty components - reduces to finding the components, the abnormalities of which could explain all the logical inconsistencies. One seeks a minimal set of faulty components (denoted a minimal diagnosis), because the trivial solution, in which all components are deemed to be faulty, always explains all inconsistencies. In the methods of the cited articles, the minimal-diagnosis problem is treated as equivalent to a minimal-hitting-set problem, which is translated from a combinatorial to a computational problem by mapping it onto the Boolean-satisfiability and integer-programming problems. The integer-programming approach taken in one of the prior methods is complete (in the sense that it is guaranteed to find a solution if one exists) and slow and yields a lower bound on the size of the minimal diagnosis. In contrast, the present approach is incomplete and fast and yields an upper bound on the size of the minimal diagnosis.

Williams, Colin↗

DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗

DOE OSTI2015

Orbitals from local RDMFT: Are they Kohn-Sham or natural orbitals?

Recently, an approximate theoretical framework was introduced, called local reduced density matrix functional theory (local-RDMFT), where functionals of the one-body reduced density matrix (1-RDM) are minimized under the additional condition that the optimal orbitals satisfy a single electron Schrödinger equation with a local potential. In the present work, we focus on the character of these optimal orbitals. In particular, we compare orbitals obtained by local-RDMFT with those obtained with the full minimization (without the extra condition) by contrasting them against the exact NOs and orbitals from a density functional calculation using the local density approximation (LDA). We find that the orbitals from local-RMDFT are very close to LDA orbitals, contrary to those of the full minimization that resemble the exact NOs. Since local RDMFT preserves the good quality of the description of strong static correlation, this finding opens the way to a mixed density/density matrix scheme, where Kohn-Sham orbitals obtain fractional occupations from a minimization of the occupation numbers using 1-RDM functionals. This will allow for a description of strong correlation at a cost only minimally higher than a density functional calculation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Path optimization by a variational reaction coordinate method. I. Development of formalism and algorithms

The development of algorithms to optimize reaction pathways between reactants and products is an active area of study. Existing algorithms typically describe the path as a discrete series of images (chain of states) which are moved downhill toward the path, using various reparameterization schemes, constraints, or fictitious forces to maintain a uniform description of the reaction path. The Variational Reaction Coordinate (VRC) method is a novel approach that finds the reaction path by minimizing the variational reaction energy (VRE) of Quapp and Bofill. The VRE is the line integral of the gradient norm along a path between reactants and products and minimization of VRE has been shown to yield the steepest descent reaction path. In the VRC method, we represent the reaction path by a linear expansion in a set of continuous basis functions and find the optimized path by minimizing the VRE with respect to the linear expansion coefficients. Improved convergence is obtained by applying constraints to the spacing of the basis functions and coupling the minimization of the VRE to the minimization of one or more points along the path that correspond to intermediates and transition states. The VRC method is demonstrated by optimizing the reaction path for the Müller-Brown surface and by finding a reaction path passing through 5 transition states and 4 intermediates for a 10 atom Lennard-Jones cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Control algorithms for dynamic attenuators

Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current modulation) without increasing peak variance. The 15-element piecewise-linear dynamic attenuator reduces dose by an average of 42%, and the perfect attenuator reduces dose by an average of 50%. Improvements in peak variance are several times larger than improvements in mean variance. Heuristic control eliminates the need for a prescan. For the piecewise-linear attenuator, the cost of heuristic control is an increase in dose of 9%. The proposed iterated WMV minimization produces results that are within a few percent of the true solution. Conclusions: Dynamic attenuators show potential for significant dose reduction. A wide class of dynamic attenuators can be accurately controlled using the described methods.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2018

Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems

We consider the numerical solution of parameterized linear systems where the system matrix, the solution, and the right-hand side are parameterized by a set of uncertain input parameters. We explore spectral methods in which the solutions are approximated in a chosen finite-dimensional subspace. It has been shown that the stochastic Galerkin projection technique fails to minimize any measure of the solution error [A. Mugler and H.-J. Starkloff, ESAIM Math. Model. Numer. Anal., 47 (2013), pp. 1237--1263]. As a remedy for this, we propose a novel stochatic least-squares Petrov--Galerkin (LSPG) method. The proposed method is optimal in the sense that it produces the solution that minimizes a weighted $\ell^2$-norm of the residual over all solutions in a given finite-dimensional subspace. Moreover, the method can be adapted to minimize the solution error in different weighted $\ell^2$-norms by simply applying a weighting function within the least-squares formulation. In addition, a goal-oriented seminorm induced by an output quantity of interest can be minimized by defining a weighting function as a linear functional of the solution. We establish optimality and error bounds for the proposed method, and extensive numerical experiments show that the weighted LSPG method outperforms other spectral methods in minimizing corresponding target weighted norms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Migration to a fully-integrated control room - 349

The nuclear industry is faced with a pressing need to reduce operating costs in order to remain competitive with other forms of electric generation. While current industry initiatives are focused on incremental gains by streamlining work processes and reducing worker burdens, very few, if any, involve significant reductions in the base workload of a nuclear plant. Migration to a fully-integrated control room affords just such an opportunity. This report describes an NPP digital instrumentation and control (I and C) system design, along with its corresponding human systems interface (HSI) design, which achieves high plant availability, while selectively applying digital equipment redundancy and integrating traditional I and C system partitions, to minimize the digital equipment needed, and thereby minimize initial installation costs and ongoing operations and maintenance (O and M) costs. An additional key component of digital equipment minimization is optimization of the digital interface to conventional plant sensors and controlled plant devices (e.g., pumps, valves), which requires no disturbance to plant cables and results in eliminating thousands of electro-mechanical relay control components. The design is rooted in the highly integrated digital technology applied to the most recent advanced light water reactors under United States (U.S.) Nuclear Regulatory Commission (NRC) design certification review and approval. While this design employs technology from new plants, that technology has been adapted to the modernization of current operating NPPs. Hence, the highly integrated digital I and C and HSI design is referred to as the compact control room digital modernization (CDM). Along with minimal digital equipment, the corresponding HSI design employs compact operator workstations with visual display units (VDU) and soft controls for both the main control room (MCR) and remote shutdown room (RSR), to immediately improve human performance and ultimately facilitate operating staff reduction. Some advanced light water reactors have demonstrated this staff reduction through full scope simulator testing of normal and abnormal plant conditions, with U.S. licensed operating crews from currently-operating U.S. plants. Digital equipment minimization, compact operator workstations, and optimized plant component interfaces that require no disturbance to field cables, also facilitate implementation of the CDM over multiple phases, most of which can be conducted during normal refueling shutdown windows. This phased implementation method includes a novel transition of the I and C, MCR and RSR with an operations centered focus. This paper presents the CDM design, along with qualitative cost/benefit comparisons to currently operating plants with conventional analog I and C and HSI technology; this generation of I and C/HSI is referred to as a conventional control room (CCR). A CCR also includes NPPs that have been upgraded with digital systems, but retain the current partitions between plant I and C systems (i.e., no I and C integration) and retain the current plant system to control board configuration of current NPP control rooms. Even though these comparisons are qualitative, a compelling case is presented for the CDM. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow

This document presents a master–slave methodology for solving the problem of optimal operation of photovoltaic (PV) distributed generators (DGs) in direct current (DC) networks. This problem was modeled using a nonlinear programming model (NLP) that considers the minimization of three different objective functions in a daily operation of the system. The first one corresponds to the minimization of the total operational cost of the system, including the energy purchasing cost to the conventional generators and maintenance costs of the PV sources; the second objective function corresponds to the reduction of the energy losses associated with the transport of energy in the network, and the third objective function is related to the minimization of the total emissions of CO2 by the conventional generators installed on the DC grid. The minimization of these objective functions is achieved by using a master–slave optimization approach through the application of the Vortex Search algorithm combined with a matrix hourly power flow. To evaluate the effectiveness and robustness of the proposed approach, two test scenarios were used, which correspond to a grid-connected and a standalone network located in two different regions of Colombia. The grid-connected system emulates the behavior of the solar resource and power demand of the city of Medellín-Antioquia, and the standalone network corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá-Choco. A numerical comparison was performed with four optimization methodologies reported in the literature: particle swarm optimization, multiverse optimizer, crow search algorithm, and salp swarm algorithm. The results obtained demonstrate that the proposed optimization approach achieved excellent solutions in terms of response quality, repeatability, and processing times.

14 SOLAR ENERGY↗