Results for “linear optimization” — Page 64

DOE OSTI2025

Data for "RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides"

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ ( R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. This result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides , providing a streamlined method for addressing genetic engineering challenges in the yeast.

gene editing↗

DOE OSTI2015

Development of Metallic Magnetic Calorimeters for Nuclear Safeguards Applications

Many nuclear safeguards applications could benefit from high-resolution gamma-ray spectroscopy achievable with metallic magnetic calorimeters. This dissertation covers the development of a system for these applications based on gamma-ray detectors developed at the University of Heidelberg. It demonstrates new calorimeters of this type, which achieved an energy resolution of 45.5 eV full-width at half-maximum at 59.54 keV, roughly ten times better than current state of the art high purity germanium detectors. This is the best energy resolution achieved with a gamma-ray metallic magnetic calorimeter at this energy to date. In addition to demonstrating a new benchmark in energy resolution, an experimental system for measuring samples with metallic magnetic calorimeters was constructed at Lawrence Livermore National Laboratory. This system achieved an energy resolution of 91.3 eV full-width at half-maximum at 59.54 keV under optimal conditions. Using this system it was possible to characterize the linearity of the response, the count-rate limitations, and the energy resolution as a function of temperature of the new calorimeter. With this characterization it was determined that it would be feasible to measure 242Pu in a mixed isotope plutonium sample. A measurement of a mixed isotope plutonium sample was performed over the course of 12 days with a single two-pixel metallic magnetic calorimeter. The relative concentration of 242Pu in comparison to other plutonium isotopes was determined by direct measurement to less than half a percent accuracy. This is comparable with the accuracy of the best-case scenario using traditional indirect methods. The ability to directly measure the relative concentration of 242Pu in a sample could enable more accurate accounting and detection of indications of undeclared activities in nuclear safeguards, a better constraint on source material in forensic samples containing plutonium, and improvements in verification in a future plutonium disposition treaty.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2011

A Model for Tow Impregnation and Consolidation for Partially Impregnated Thermoset Prepregs

The formation and transport of voids in composite materials remains a key research area in composite manufacturing science. Knowledge of how voids, resin, and fiber reinforcement propagate throughout a composite material continuum from green state to cured state during an automated tape layup process is key to minimizing defects induced by void-initiated stress concentrations under applied loads for a wide variety of composite applications. This paper focuses on modeling resin flow in a deforming fiber tow during an automated process of partially impregnated thermoset prepreg composite material tapes. In this work, a tow unit cell based model has been presented that determines the consolidation and impregnation of a thermoset prepreg tape under an input pressure profile. A parametric study has been performed to characterize the behavior of varying tow speed and compaction forces on the degree of consolidation. Results indicate that increased tow consolidation is achieved with slower tow speeds and higher compaction forces although the relationship is not linear. The overall modeling of this project is motivated to address optimization of the 'green state' composite properties and processing parameters to reduce or eliminate 'cured state' defects, such as porosity and de-lamination. This work is partially funded by the Department of Energy under Award number DE-EE0001367.

36 MATERIALS SCIENCE↗

DOE OSTI2011

A Model for Tow Impregnation and Consolidation for Partially Impregnated Thermoset Prepregs

The formation and transport of voids in composite materials remains a key research area in composite manufacturing science. Knowledge of how voids, resin, and fiber reinforcement propagate throughout a composite material continuum from green state to cured state during an automated tape layup process is key to minimizing defects induced by void-initiated stress concentrations under applied loads for a wide variety of composite applications. This paper focuses on modeling resin flow in a deforming fiber tow during an automated process of partially impregnated thermoset prepreg composite material tapes. In this work, a tow unit cell based model has been presented that determines the consolidation and impregnation of a thermoset prepreg tape under an input pressure profile. A parametric study has been performed to characterize the behavior of varying tow speed and compaction forces on the degree of consolidation. Results indicate that increased tow consolidation is achieved with slower tow speeds and higher compaction forces although the relationship is not linear. The overall modeling of this project is motivated to address optimization of the 'green state' composite properties and processing parameters to reduce or eliminate 'cured state' defects, such as porosity and de-lamination. This work is partially funded by the Department of Energy under Award number DE-EE0001367.

36 MATERIALS SCIENCE↗

DOE OSTI2015

A Bound- and Equality-Constrained Quadratic Programming Method for Image Reconstruction

Image deblurring is modeled as an ill-posed, linear inverse problem and can be written in terms of an optimization problem. By adding bound and equality constraints and/or penalty terms to the objective function, the problem is regularized and a viable solution exists; however, there are few methods available for solving such constrained problems. Here we formulate two regularized solutions into constrained optimization problems and adapt an iterative augmented Lagrangian solver. Results are shown on synthetic data in one- and two-dimensions, as well as on a radiograph used to calibrate the transmission curve of a pulsed power X-ray source at a U.S. Department of Energy radiography facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasifiction combined sycle (IGCC) power plant with CO2 capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2012

Thermodynamic Metrics and Optimal Paths

A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Adaptation of the CVT algorithm for catheter optimization in high dose rate brachytherapy

Purpose: An innovative, simple, and fast method to optimize the number and position of catheters is presented for prostate and breast high dose rate (HDR) brachytherapy, both for arbitrary templates or template-free implants (such as robotic templates).Methods: Eight clinical cases were chosen randomly from a bank of patients, previously treated in our clinic to test our method. The 2D Centroidal Voronoi Tessellations (CVT) algorithm was adapted to distribute catheters uniformly in space, within the maximum external contour of the planning target volume. The catheters optimization procedure includes the inverse planning simulated annealing algorithm (IPSA). Complete treatment plans can then be generated from the algorithm for different number of catheters. The best plan is chosen from different dosimetry criteria and will automatically provide the number of catheters and their positions. After the CVT algorithm parameters were optimized for speed and dosimetric results, it was validated against prostate clinical cases, using clinically relevant dose parameters. The robustness to implantation error was also evaluated. Finally, the efficiency of the method was tested in breast interstitial HDR brachytherapy cases.Results: The effect of the number and locations of the catheters on prostate cancer patients was studied. Treatment plans with a better or equivalent dose distributions could be obtained with fewer catheters. A better or equal prostate V100 was obtained down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of prostate V100 and D90. Implantation errors up to 3 mm were acceptable since no statistical difference was found when compared to 0 mm error (p > 0.05). No significant difference in dosimetric indices was observed for the different combination of parameters within the CVT algorithm. A linear relation was found between the number of random points and the optimization time of the CVT algorithm. Because the computation time decrease with the number of points and that no effects were observed on the dosimetric indices when varying the number of sampling points and the number of iterations, they were respectively fixed to 2500 and to 100. The computation time to obtain ten complete treatments plans ranging from 9 to 18 catheters, with the corresponding dosimetric indices, was 90 s. However, 93% of the computation time is used by a research version of IPSA. For the breast, on average, the Radiation Therapy Oncology Group recommendations would be satisfied down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of V100, dose homogeneity index, and D90.Conclusions: The authors have devised a simple, fast and efficient method to optimize the number and position of catheters in interstitial HDR brachytherapy. The method was shown to be robust for both prostate and breast HDR brachytherapy. More importantly, the computation time of the algorithm is acceptable for clinical use. Ultimately, this catheter optimization algorithm could be coupled with a 3D ultrasound system to allow real-time guidance and planning in HDR brachytherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

Investigations into the Effect of Current Velocity on Amidoxime-Based Polymeric Uranium Adsorbent Performance

The Fuel Resources Program at the U.S. Department of Energy’s (DOE), Office of Nuclear Energy (DOE-NE) is developing adsorbent technology to extract uranium from seawater. This technology is being developed to provide a sustainable and economically viable supply of uranium fuel for nuclear reactors (DOE, 2010). Among the key environmental variables to understand for adsorbent deployment in the coastal ocean is what effect flow-rates or linear velocity has on uranium adsorption capacity. The goal is to find a flow conditions that optimize uranium adsorption capacity in the shortest exposure time. Understanding these criteria will be critical in choosing a location for deployment of a marine adsorbent farm. The objective of this study was to identify at what linear velocity the adsorption kinetics for uranium extraction starts to drop off due to limitations in mass transport of uranium to the surface of the adsorbent fibers. Two independent laboratory-based experimental approaches using flow-through columns and recirculating flumes for adsorbent exposure were used to assess the effect of flow-rate (linear velocity) on the kinetic uptake of uranium on amidoxime-based polymeric adsorbent material. Time series observations over a 56 day period were conducted with flow-through columns over a 35-fold range in linear velocity from 0.29 to 10.2 cm/s, while the flume study was conducted over a narrower 11-fold range, from 0.48 to 5.52 cm/s. These ranges were specifically chosen to focus on the lower end of oceanic currents and expand above and below the linear velocity of ~ 2.5 cm/s adopted for marine testing of adsorbent material at PNNL.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Frame average optimization of cine-mode EPID images used for routine clinical in vivo patient dose verification of VMAT deliveries

Purpose: The in vivo 3D dose delivered to a patient during volumetric modulated arc therapy (VMAT) delivery can be calculated using electronic portal imaging device (EPID) images. These images must be acquired in cine-mode (i.e., “movie” mode) in order to capture the time-dependent delivery information. The angle subtended by each cine-mode EPID image during an arc can be changed via the frame averaging number selected within the image acquisition software. A large frame average number will decrease the EPID’s angular resolution and will result in a decrease in the accuracy of the dose information contained within each image. Alternatively, less EPID images acquired per delivery will decrease the overall 3D patient dose calculation time, which is appealing for large-scale clinical implementation. Therefore, the purpose of this study was to determine the optimal frame average value per EPID image, defined as the highest frame averaging that can be used without an appreciable loss in 3D dose reconstruction accuracy for VMAT treatments. Methods: Six different VMAT plans and six different SBRT-VMAT plans were delivered to an anthropomorphic phantom. Delivery was carried out on a Varian 2300ix model linear accelerator (Linac) equipped with an aS1000 EPID running at a frame acquisition rate of 7.5 Hz. An additional PC was set up at the Linac console area, equipped with specialized frame-grabber hardware and software packages allowing continuous acquisition of all EPID frames during delivery. Frames were averaged into “frame-averaged” EPID images using MATLAB. Each frame-averaged data set was used to calculate the in vivo dose to the patient and then compared to the single EPID frame in vivo dose calculation (the single frame calculation represents the highest possible angular resolution per EPID image). A mean percentage dose difference of low dose (<20% prescription dose) and high dose regions (>80% prescription dose) was calculated for each frame averaged scenario for each plan. The authors defined their unacceptable loss of accuracy as no more than a ±1% mean dose difference in the high dose region. Optimal frame average numbers were then determined as a function of the Linac’s average gantry speed and the dose per fraction. Results: The authors found that 9 and 11 frame averages were suitable for all VMAT and SBRT-VMAT treatments, respectively. This resulted in no more than a 1% loss to any of the dose region’s mean percentage difference when compared to the single frame reconstruction. The optimized number was dependent on the treatment’s dose per fraction and was determined to be as high as 14 for 12 Gy/fraction (fx), 15 for 8 Gy/fx, 11 for 6 Gy/fx, and 9 for 2 Gy/fx. Conclusions: The authors have determined an optimal EPID frame averaging number for multiple VMAT-type treatments. These are given as a function of the dose per fraction and average gantry speed. These optimized values are now used in the authors’ clinical, 3D, in vivo patient dosimetry program. This provides a reduction in calculation time while maintaining the authors’ required level of accuracy in the dose reconstruction.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Explicit model predictive control through robust optimization

A strategy that calculates an explicit state feedback policy to regulate constrained uncertain discrete‐time uncertain linear systems is presented. We consider uncertain processes, affected by box‐bounded multiplicative uncertainty as well as bounded additive uncertainty with linear state and inputs constraints. The proposed method includes (i) the calculation of a terminal set constraint and (ii) the robust reformulation of state constraints in the prediction horizon. These features allow the derivation of the desired policy by solving a single multiparametric quadratic programming problem that guarantees feasible operation in the presence of uncertainty. Additionally, we employ variable and constraint elimination approaches to enhance the computational performance of the strategy. We demonstrate the steps and benefits of these developments with a numerical example and a chemical engineering case study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Two-dimensional inverse planning and delivery with a preclinical image guided microirradiator

Purpose: Recent advances in preclinical radiotherapy systems have provided the foundation for scaling many of the elements of clinical radiation therapy practice to the dimensions and energy demanded in small animal studies. Such systems support the technical capabilities to accurately deliver highly complex dose distributions, but methods to optimize and deliver such distributions remain in their infancy. This study developed an optimization method based on empirically measured two-dimensional dose kernel measurements to deliver arbitrary planar dose distributions on a recently developed small animal radiotherapy platform.Methods: A two-dimensional dose kernel was measured with repeated radiochromic film measurements for the circular 1 mm diameter fixed collimator of the small animal radiotherapy system at 1 cm depth in a solid water phantom. This kernel was utilized in a sequential quadratic programming optimization framework to determine optimal beam positions and weights to deliver an arbitrary desired dose distribution. The positions and weights were then translated to a set of stage motions to automatically deliver the optimized dose distribution. End-to-end efficacy of the framework was quantified through five repeated deliveries of two dosimetric challenges: (1) a 5 mm radius bullseye distribution, and (2) a “sock” distribution contained within a 9 × 13 mm bounding box incorporating rectangular, semicircular, and exponentially decaying geometric constructs and a rectangular linear dose gradient region. These two challenges were designed to gauge targeting, geometric, and dosimetric fidelity.Results: Optimization of the bullseye and sock distributions required 2.1 and 5.9 min and utilized 50 and 77 individual beams for delivery, respectively. Automated delivery of the resulting optimized distributions, validated using radiochromic film measurements, revealed an average targeting accuracy of 0.32 mm, and a dosimetric delivery error along four line profiles taken through the sock distribution of 3.9%. Mean absolute delivery error across the 0–1 Gy linear dose gradient over 7.5 mm was 0.01 Gy.Conclusions: The work presented here demonstrates the potential for complex dose distributions to be planned and automatically delivered with millimeter scale heterogeneity at submillimeter accuracy. This capability establishes the technical foundation for preclinical validation of biologically guided radiotherapy investigations and development of unique radiobiological experiments.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2014

SU-C-17A-07: The Development of An MR Accelerator-Enabled Planning-To-Delivery Technique for Stereotactic Palliative Radiotherapy Treatment of Spinal Metastases

Purpose: To develop an MR accelerator-enabled online planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases. The technical challenges include; automated stereotactic treatment planning, online MR-based dose calculation and MR guidance during treatment. Methods: Using the CT data of 20 patients previously treated at our institution, a class solution for automated treatment planning for spinal bone metastases was created. For accurate dose simulation right before treatment, we fused geometrically correct online MR data with pretreatment CT data of the target volume (TV). For target tracking during treatment, a dynamic T2-weighted TSE MR sequence was developed. An in house developed GPU based IMRT optimization and dose calculation algorithm was used for fast treatment planning and simulation. An automatically generated treatment plan developed with this treatment planning system was irradiated on a clinical 6 MV linear accelerator and evaluated using a Delta4 dosimeter. Results: The automated treatment planning method yielded clinically viable plans for all patients. The MR-CT fusion based dose calculation accuracy was within 2% as compared to calculations performed with original CT data. The dynamic T2-weighted TSE MR Sequence was able to provide an update of the anatomical location of the TV every 10 seconds. Dose calculation and optimization of the automatically generated treatment plans using only one GPU took on average 8 minutes. The Delta4 measurement of the irradiated plan agreed with the dose calculation with a 3%/3mm gamma pass rate of 86.4%. Conclusions: The development of an MR accelerator-enabled planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases was presented. Future work will involve developing an intrafraction motion adaptation strategy, MR-only dose calculation, radiotherapy quality-assurance in a magnetic field, and streamlining the entire treatment process on an MR accelerator.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Feasibility of a unified approach to intensity-modulated radiation therapy and volume-modulated arc therapy optimization and delivery

Purpose: To study the feasibility of unified intensity-modulated arc therapy (UIMAT) which combines intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) optimization and delivery to produce superior radiation treatment plans, both in terms of dose distribution and efficiency of beam delivery when compared with either VMAT or IMRT alone. Methods: An inverse planning algorithm for UIMAT was prototyped within the PINNACLE treatment planning system (Philips Healthcare). The IMRT and VMAT deliveries are unified within the same arc, with IMRT being delivered at specific gantry angles within the arc. Optimized gantry angles for the IMRT and VMAT phases are assigned automatically by the inverse optimization algorithm. Optimization of the IMRT and VMAT phases is done simultaneously using a direct aperture optimization algorithm. Five treatment plans each for prostate, head and neck, and lung were generated using a unified optimization technique and compared with clinical IMRT or VMAT plans. Delivery verification was performed with an ArcCheck phantom (Sun Nuclear) on a Varian TrueBeam linear accelerator (Varian Medical Systems). Results: In this prototype implementation, the UIMAT plans offered the same target dose coverage while reducing mean doses to organs at risk by 8.4% for head-and-neck cases, 5.7% for lung cases, and 3.5% for prostate cases, compared with the VMAT or IMRT plans. In addition, UIMAT can be delivered with similar efficiency as VMAT. Conclusions: In this proof-of-concept work, a novel radiation therapy optimization and delivery technique that interlaces VMAT or IMRT delivery within the same arc has been demonstrated. Initial results show that unified VMAT/IMRT has the potential to be superior to either standard IMRT or VMAT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Efficient shallow Ritz method for 1D diffusion problems

This paper studies the shallow Ritz method for solving the one-dimensional diffusion problem. It is shown that the shallow Ritz method improves the order of approximation dramatically for non-smooth problems. To realize this optimal or nearly optimal order of the shallow Ritz approximation, we develop a damped block Newton (dBN) method that alternates between updates of the linear and non-linear parameters. Per each iteration, the linear and the non-linear parameters are updated by exact inversion and one step of a modified, damped Newton method applied to a reduced non-linear system, respectively. The computational cost of each dBN iteration is $\mathcal{O}$(n). Starting with the non-linear parameters as a uniform partition of the interval, numerical experiments show that the dBN is capable of efficiently moving mesh points to nearly optimal locations. In conclusion, to improve the efficiency of the dBN further, we propose an adaptive damped block Newton (AdBN) method by combining the dBN with the adaptive neuron enhancement (ANE) method [28].

Diffusion problems↗

DOE OSTI2017

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarm rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

SU-F-T-35: Optimization of Bladder and Rectal Doses Using a Multi-Lumen Intracavitary Applicator for Gynecological Brachytherapy

Purpose: Radiation dose delivery for endometrial cancer using HDR techniques is limited by dose to bladder and rectum. A dosimetric study was performed using Varian Capri vaginal brachytherapy applicator to determine the optimal channel configuration which minimizes dose to bladder and rectum, while providing good target coverage. Methods: A total of 17 patients, 63 plans clinically delivered, and 252 simulated plans using Varian BrachyVision planning system were generated to investigate optimal channel configuration which results in minimum dose to bladder and rectum while providing adequate target coverage. The Capri applicator consists of 13 lumens arranged in two concentric rings, one central lumen and six lumens per ring. Manual dose shaping is invariably required to lower the dose to critical organs. Three-dimensional plans were simulated for 4 channel arrangements, all 13 channels, channel 12 o’clock (close to bladder) and 6 o’clock (close to rectum) deactivated, central channel deactivated, and central channel in addition to 12 o’clock and 6 o’clock deactivated. A relationship between V100, the volume that receives the prescribed dose, and the amount of curie-seconds required to deliver it, was established. Results: Using all 13 channels results in maximum dose to bladder and rectum. Deactivating central channel in addition to 12 o’clock and 6 o’clock resulted in minimizing bladder and rectum doses but compromised target coverage. The relationship between V100, the volume that receives the prescribed dose, and the curie seconds was found to be linear. Conclusion: Deactivating channels 12 o’clock and 6 o’clock was shown to be the optimal configuration leading to minimum dose to bladder and rectum without compromising target coverage. The linear relationship between V100 and the curie- seconds can be used as a verification parameter.

60 APPLIED LIFE SCIENCES↗