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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

The suitability of selected multidisciplinary design and optimization techniques to conceptual aerospace vehicle design

Four methods for preliminary aerospace vehicle design are reviewed. The first three methods (classical optimization, system decomposition, and system sensitivity analysis (SSA)) employ numerical optimization techniques and numerical gradients to feed back changes in the design variables. The optimum solution is determined by stepping through a series of designs toward a final solution. Of these three, SSA is argued to be the most applicable to a large-scale highly coupled vehicle design where an accurate minimum of an objective function is required. With SSA, several tasks can be performed in parallel. The techniques of classical optimization and decomposition can be included in SSA, resulting in a very powerful design method. The Taguchi method is more of a 'smart' parametric design method that analyzes variable trends and interactions over designer specified ranges with a minimum of experimental analysis runs. Its advantages are its relative ease of use, ability to handle discrete variables, and ability to characterize the entire design space with a minimum of analysis runs.

Olds, John R.↗
NASA NTRS2003

Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft

The neural network and regression methods of NASA Glenn Research Center s COMETBOARDS design optimization testbed were used to generate approximate analysis and design models for a subsonic aircraft operating at Mach 0.85 cruise speed. The analytical model is defined by nine design variables: wing aspect ratio, engine thrust, wing area, sweep angle, chord-thickness ratio, turbine temperature, pressure ratio, bypass ratio, fan pressure; and eight response parameters: weight, landing velocity, takeoff and landing field lengths, approach thrust, overall efficiency, and compressor pressure and temperature. The variables were adjusted to optimally balance the engines to the airframe. The solution strategy included a sensitivity model and the soft analysis model. Researchers generated the sensitivity model by training the approximators to predict an optimum design. The trained neural network predicted all response variables, within 5-percent error. This was reduced to 1 percent by the regression method. The soft analysis model was developed to replace aircraft analysis as the reanalyzer in design optimization. Soft models have been generated for a neural network method, a regression method, and a hybrid method obtained by combining the approximators. The performance of the models is graphed for aircraft weight versus thrust as well as for wing area and turbine temperature. The regression method followed the analytical solution with little error. The neural network exhibited 5-percent maximum error over all parameters. Performance of the hybrid method was intermediate in comparison to the individual approximators. Error in the response variable is smaller than that shown in the figure because of a distortion scale factor. The overall performance of the approximators was considered to be satisfactory because aircraft analysis with NASA Langley Research Center s FLOPS (Flight Optimization System) code is a synthesis of diverse disciplines: weight estimation, aerodynamic analysis, engine cycle analysis, propulsion data interpolation, mission performance, airfield length for landing and takeoff, noise footprint, and others.

Hopkins, Dale A.↗
DOE OSTI2024

Efficient Parameterization of Density Functional Tight-Binding for 5 f -Elements: A Th–O Case Study

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th–O system, which was subsequently applied to the study of ThO 2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO 2 . Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2010

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.

Rash, James L.↗
NASA NTRS2014

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

ground stations↗
DOE OSTI2015

System, method, and computer program product for bulk synchronous binary program translation and optimization

A system, method, and computer program product are provided for. The method includes the steps of executing a block of translated binary instructions by multiple threads and gathering profiling data during execution of the block of translated binary instructions. The multiple threads are then synchronized at a barrier instruction associated with the block of translated binary instructions and the block of translated binary instructions is replaced with optimized binary instructions, where the optimized binary instructions are produced based on the profiling data.

Diamos, Gregory Frederick↗
DOE OSTI2014

TH-C-BRD-03: Determining the Optimal Collimator Position for Collimated Pencil Beam Scanning Proton Therapy

Purpose: There has been a growing interest in applying collimation to pencil beam scanning (PBS) proton therapy in order to sharpen the lateral dose falloff out of the target, especially at low energies. Currently, there is not a method to optimally determine the collimation position or margin around the target. A uniform margin would not be ideal due to the fact that an incoming symmetric pencil beam, after being intercepted by a collimator near the target boundary, will become asymmetric and experience a lateral shift away from its original spot location, leaving the target insufficiently covered. We demonstrate a method that optimally determines the collimator position on a per-spot basis, in order to maximize target dose while minimizing normal tissue dose. Methods: A library of collimated pencil beams were obtained through Monte Carlo simulation with a collimator placed at varying distances from the central axis of an incoming symmetrical pencil beam of 118 MeV and 5 mm sigma-in-air. Two-dimensional treatment plans were then created using this library of collimated pencil beams. For each spot position in a treatment plan, the collimator position was optimally determined in such a way that the resultant pencil beam maximized the ratio of in-target dose and out-of-target dose. For comparison, un-collimated treatment plans were also computed. Results: The spot-by-spot optimally determined collimator positions allowed the reduction of normal tissue dose while maintaining the same target coverage as un-collimated PBS. Quantitatively, the mean dose outside of the target was reduced by approximately 40% as compared to the plan without collimation. Conclusion: The proposed method determines the optimal collimator position for each spot in collimated PBS proton therapy. The use of a collimator will improve PBS dose distributions achievable today and will continue to be the subject of future investigations.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Nanostructured carbon materials for adsorption of methane and other gases

Provided are methods for storing gases on porous adsorbents, methods for optimizing the storage of gases on porous adsorbents, methods of making porous adsorbents, and methods of gas storage of optimized compositions, as in systems containing porous adsorbents and gas adsorbed on the surface of the porous adsorbent. The disclosed methods and systems feature a constant or increasing isosteric enthalpy of adsorption as a function of uptake of the gas onto the exposed surface of a porous adsorbent. Adsorbents with a porous geometry and surface dimensions suited to a particular adsorbate are exposed to the gas at elevated pressures in the specific regime where n/V (density) is larger than predicted by the ideal gas law by more than several percent.

03 NATURAL GAS↗
DOE OSTI2014

Numerical Studies of Optimization and Aberration Correction Methods for the Preliminary Demonstration of the Parametric Ionization Cooling (PIC) Principle in the Twin Helix Muon Cooling Channel

Muon colliders have been proposed for the next generation of particle accelerators that study high-energy physics at the energy and intensity frontiers. In this paper we study a possible implementation of muon ionization cooling, Parametric-resonance Ionization Cooling (PIC), in the twin helix channel. The resonant cooling method of PIC offers the potential to reduce emittance beyond that achievable with ionization cooling with ordinary magnetic focusing. We examine optimization of a variety of parameters, study the nonlinear dynamics in the twin helix channel and consider possible methods of aberration correction.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Sci—Thur PM: Planning and Delivery — 03: Automated delivery and quality assurance of a modulated electron radiation therapy plan

Modulated electron radiation therapy (MERT) offers the potential to improve healthy tissue sparing through increased dose conformity. Challenges remain, however, in accurate beamlet dose calculation, plan optimization, collimation method and delivery accuracy. In this work, we investigate the accuracy and efficiency of an end-to-end MERT plan and automated-delivery workflow for the electron boost portion of a previously treated whole breast irradiation case. Dose calculations were performed using Monte Carlo methods and beam weights were determined using a research-based treatment planning system capable of inverse optimization. The plan was delivered to radiochromic film placed in a water equivalent phantom for verification, using an automated motorized tertiary collimator. The automated delivery, which covered 4 electron energies, 196 subfields and 6183 total MU was completed in 25.8 minutes, including 6.2 minutes of beam-on time with the remainder of the delivery time spent on collimator leaf motion and the automated interfacing with the accelerator in service mode. The delivery time could be reduced by 5.3 minutes with minor electron collimator modifications and the beam-on time could be reduced by and estimated factor of 2–3 through redesign of the scattering foils. Comparison of the planned and delivered film dose gave 3%/3 mm gamma pass rates of 62.1, 99.8, 97.8, 98.3, and 98.7 percent for the 9, 12, 16, 20 MeV, and combined energy deliveries respectively. Good results were also seen in the delivery verification performed with a MapCHECK 2 device. The results showed that accurate and efficient MERT delivery is possible with current technologies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2018

Method and Apparatus for Providing In-Flight Pilot Interface for Trajectory Optimization

Systems and methods of an in-cockpit flight trajectory modification system for an aircraft are provided. A receiver is capable of receiving flight-related hazard information. A traffic aware planner (TAP) module is operably connected to the receiver to receive the flight-related hazard information. A user interface device is operably connected to the TAP module on board the aircraft to provide trajectory information associated with the aircraft and to receive user input corresponding to a request for a revised trajectory. A TAP application is capable of calculating one or more revised trajectories for the aircraft based at least on active trajectory information of the aircraft and the flight-related hazard information. The user interface device may be configured to display information related to the one or more revised trajectories, including a graphic display of the active trajectory and at least one revised trajectory in a visualization panel of the user interface device.

Burke, Kelly Ann↗
DOE OSTI2014

TH-C-BRD-10: An Evaluation of Three Robust Optimization Approaches in IMPT Treatment Planning

Purpose: Various robust optimization approaches have been proposed to ensure the robustness of intensity modulated proton therapy (IMPT) in the face of uncertainty. In this study, we aim to investigate the performance of three classes of robust optimization approaches regarding plan optimality and robustness. Methods: Three robust optimization models were implemented in our in-house IMPT treatment planning system: 1) L2 optimization based on worst-case dose; 2) L2 optimization based on minmax objective; and 3) L1 optimization with constraints on all uncertain doses. The first model was solved by a L-BFGS algorithm; the second was solved by a gradient projection algorithm; and the third was solved by an interior point method. One nominal scenario and eight maximum uncertainty scenarios (proton range over and under 3.5%, and setup error of 5 mm for x, y, z directions) were considered in optimization. Dosimetric measurements of optimized plans from the three approaches were compared for four prostate cancer patients retrospectively selected at our institution. Results: For the nominal scenario, all three optimization approaches yielded the same coverage to the clinical treatment volume (CTV) and the L2 worst-case approach demonstrated better rectum and bladder sparing than others. For the uncertainty scenarios, the L1 approach resulted in the most robust CTV coverage against uncertainties, while the plans from L2 worst-case were less robust than others. In addition, we observed that the number of scanning spots with positive MUs from the L2 approaches was approximately twice as many as that from the L1 approach. This indicates that L1 optimization may lead to more efficient IMPT delivery. Conclusion: Our study indicated that the L1 approach best conserved the target coverage in the face of uncertainty but its resulting OAR sparing was slightly inferior to other two approaches.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-EF-204-09: A Preliminary Method of Risk-Informed Optimization of Tube Current Modulation for Dose Reduction in CT

Purpose: X-rays from CT scans can increase cancer risk to patients. Lifetime Attributable Risk of Cancer Incidence for adult patients has been investigated and shown to decrease as patient age. However, a new risk model shows an increasing risk trend for several radiosensitive organs for middle age patients. This study investigates the feasibility of a general method for optimizing tube current modulation (TCM) functions to minimize risk by reducing radiation dose to radiosensitive organs of patients. Methods: Organ-based TCM has been investigated in literature for eye lens dose and breast dose. Adopting the concept in organ-based TCM, this study seeks to find an optimized tube current for minimal total risk to breasts and lungs by reducing dose to these organs. The contributions of each CT view to organ dose are determined through simulations of CT scan view-by-view using a GPU-based fast Monte Carlo code, ARCHER. A Linear Programming problem is established for tube current optimization, with Monte Carlo results as weighting factors at each view. A pre-determined dose is used as upper dose boundary, and tube current of each view is optimized to minimize the total risk. Results: An optimized tube current is found to minimize the total risk of lungs and breasts: compared to fixed current, the risk is reduced by 13%, with breast dose reduced by 38% and lung dose reduced by 7%. The average tube current is maintained during optimization to maintain image quality. In addition, dose to other organs in chest region is slightly affected, with relative change in dose smaller than 10%. Conclusion: Optimized tube current plans can be generated to minimize cancer risk to lungs and breasts while maintaining image quality. In the future, various risk models and greater number of projections per rotation will be simulated on phantoms of different gender and age. National Institutes of Health R01EB015478.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-BRC-01: An Automatic Beam Model Commissioning Method for Monte Carlo Simulations in Pencil-Beam Scanning Proton Therapy

Purpose: Monte Carlo (MC) simulation is typically regarded as the most accurate dose calculation method for proton therapy. Yet for real clinical cases, the overall accuracy also depends on that of the MC beam model. Commissioning a beam model to faithfully represent a real beam requires finely tuning a set of model parameters, which could be tedious given the large number of pencil beams to commmission. This abstract reports an automatic beam-model commissioning method for pencil-beam scanning proton therapy via an optimization approach. Methods: We modeled a real pencil beam with energy and spatial spread following Gaussian distributions. Mean energy, and energy and spatial spread are model parameters. To commission against a real beam, we first performed MC simulations to calculate dose distributions of a set of ideal (monoenergetic, zero-size) pencil beams. Dose distribution for a real pencil beam is hence linear superposition of doses for those ideal pencil beams with weights in the Gaussian form. We formulated the commissioning task as an optimization problem, such that the calculated central axis depth dose and lateral profiles at several depths match corresponding measurements. An iterative algorithm combining conjugate gradient method and parameter fitting was employed to solve the optimization problem. We validated our method in simulation studies. Results: We calculated dose distributions for three real pencil beams with nominal energies 83, 147 and 199 MeV using realistic beam parameters. These data were regarded as measurements and used for commission. After commissioning, average difference in energy and beam spread between determined values and ground truth were 4.6% and 0.2%. With the commissioned model, we recomputed dose. Mean dose differences from measurements were 0.64%, 0.20% and 0.25%. Conclusion: The developed automatic MC beam-model commissioning method for pencil-beam scanning proton therapy can determine beam model parameters with satisfactory accuracy.

60 APPLIED LIFE SCIENCES↗
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↗