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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61

TEX-Chlorine Assemblies: Highly Enriched Uranium Plates with Sodium Chloride Absorbers Using Polyethylene Moderator and Polyethylene Reflector

This evaluation documents highly enriched uranium (HEU) experimental critical configurations with polyethylene moderators and sodium chloride absorbers conducted as part of the United States Nuclear Criticality Safety Program’s Thermal/Epithermal eXperiments (TEX) program. HEU-MET-MIXED-021 provides the benchmark evaluation of five TEX experiments designed to establish baseline configurations with HEU Jemima plates moderated by high density polyethylene (HDPE). The TEX-HEU experiments were designed to cover five different fission energy regimes by varying the thickness of the interstitial HDPE moderator, with varying fractions of thermal, intermediate, and fast fissions, and to be easily modified to accommodate test materials of interest. HEU-MET-INTER-013 documents the first TEX-HEU variation, incorporating hafnium in seven different experimental configurations. This evaluation covers an additional variant that incorporates absorber plates of compacted high-purity sodium chloride salt. These experiments were motivated by a criticality safety need for validation data for uranium purification by means of electrorefining with chloride salts, especially thermal and intermediate energy configurations resulting from moderator upset conditions, and their design was optimized by matching sensitivity profiles from application cases. All three experimental configurations are judged to be acceptable as benchmark cases. The main parameter varied between the configurations is the thickness of the polyethylene moderators and the sodium chloride absorbers between the HEU plates. Varying the thickness of the polyethylene tunes the neutron energy spectrum between majority thermal (Case 1 and 2) and intermediate (Case 3). The fission fractions, presented in Table 1, are determined calculationally. Case 3 is cross listed as HEU-MET-INTER-014.

42 ENGINEERING↗

Aeroelastic Trim Drag Optimization of Mach 0.745 Transonic Truss-Braced Wing Aircraft with Variable-Camber Continuous Trailing-Edge Flap

This paper presents an aeroelastic trim drag optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft with the Variable-Camber Continuous Trailing-Edge Flap (VCCTEF). An aero-structural analysis solver VSPAERO with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections coupled to finite-element code BEAM3D is developed to provide a rapid aircraft aeroelastic performance evaluation. The VSPAERO model has been validated against wind tunnel test data. Aeroelastic trim drag optimization studies are conducted for a VCCTEF configuration with 6-spanwise sections. Three different flight conditions corresponding to Mach 0.745 are selected for the TTBW aircraft aeroelastic trim drag optimization at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized VCCTEF deflection achieves a drag reduction of about 9.1 counts, 5.9 counts, and 11.8 counts corresponding to the lift coefficients 0.68, 0.73, and 0.78, respectively. A high-fidelity CFD solver FUN3D is used to validate the aeroelastic trim drag optimization.

Aeroelastic trim drag↗

High-Lift Optimization Design Using Neural Networks on a Multi-Element Airfoil

The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag, and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural networks were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 83% compared with traditional gradient-based optimization procedures for multiple optimization runs.

Greenman, Roxana M.↗

Applying design principles to fusion reactor configurations for propulsion in space

The application of fusion power to space propulsion requires rethinking the engineering-design solution to controlled-fusion energy. Whereas the unit cost of electricity (COE) drives the engineering-design solution for utility-based fusion reactor configurations; initial mass to low earth orbit (IMLEO), specific jet power (kW(thrust)/kg(engine)), and reusability drive the engineering-design solution for successful application of fusion power to space propulsion. We applied three design principles (DP's) to adapt and optimize three candidate-terrestrial-fusion-reactor configurations for propulsion in space. The three design principles are: provide maximum direct access to space for waste radiation, operate components as passive radiators to minimize cooling-system mass, and optimize the plasma fuel, fuel mix, and temperature for best specific jet power. The three candidate terrestrial fusion reactor configurations are: the thermal barrier tandem mirror (TBTM), field reversed mirror (FRM), and levitated dipole field (LDF). The resulting three candidate space fusion propulsion systems have their IMLEO minimized and their specific jet power and reusability maximized. We performed a preliminary rating of these configurations and concluded that the leading engineering-design solution to space fusion propulsion is a modified TBTM that we call the Mirror Fusion Propulsion System (MFPS).

Carpenter, Scott A.↗

Elastically Shaped Wing Optimization and Aircraft Concept for Improved Cruise Efficiency

This paper presents the findings of a study conducted tn 2010 by the NASA Innovation Fund Award project entitled "Elastically Shaped Future Air Vehicle Concept". The study presents three themes in support of meeting national and global aviation challenges of reducing fuel burn for present and future aviation systems. The first theme addresses the drag reduction goal through innovative vehicle configurations via non-planar wing optimization. Two wing candidate concepts have been identified from the wing optimization: a drooped wing shape and an inflected wing shape. The drooped wing shape is a truly biologically inspired wing concept that mimics a seagull wing and could achieve about 5% to 6% drag reduction, which is aerodynamically significant. From a practical perspective, this concept would require new radical changes to the current aircraft development capabilities for new vehicles with futuristic-looking wings such as this concept. The inflected wing concepts could achieve between 3% to 4% drag reduction. While the drag reduction benefit may be less, the inflected-wing concept could have a near-term impact since this concept could be developed within the current aircraft development capabilities. The second theme addresses the drag reduction goal through a new concept of elastic wing shaping control. By aeroelastically tailoring the wing shape with active control to maintain optimal aerodynamics, a significant drag reduction benefit could be realized. A significant reduction in fuel burn for long-range cruise from elastic wing shaping control could be realized. To realize the potential of the elastic wing shaping control concept, the third theme emerges that addresses the drag reduction goal through a new aerodynamic control effector called a variable camber continuous trailing edge flap. Conventional aerodynamic control surfaces are discrete independent surfaces that cause geometric discontinuities at the trailing edge region. These discontinuities promote vorticities which result in drag rises as well as noise sources. The variable camber trailing edge flap concept could provide a substantial drag reduction benefit over a conventional discrete flap system. Aerodynamic simulations show a drag reduction of over 50% could be achieved with the flap concept over a conventional discrete flap system.

Nguyen, Nhan↗

Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (RL) [Monte Carlo Tree Search (MCTS)] based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low-dimensional materials. Using a representative case of two-dimensional MoS 2 , we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5 to 8% S vacancies)-the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS 2 are discussed. In this study, we introduce a RL strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parametric analysis on optimized design of hybrid solar power plants

There is increasing interest in utility-scale solar power plants with storage which can flexibly dispatch renewable energy to the grid. However, plant design possesses many degrees of freedom and non-obvious trade-offs in performance. Software tools can estimate or optimize the performance of a specific plant configuration under market and weather conditions of interest; the associated cost parameters and operating assumptions strongly influence estimates of plant performance and decisions regarding optimal sizing. We employ the National Renewable Energy Laboratory's Hybrid Optimization and Performance Platform, which incorporates optimal dispatch when evaluating plant performance, and investigate the sensitivity to weather and market conditions, operating limitations, and the presence of a capacity-based incentive. We demonstrate changes in plant performance and optimal sizing with respect to these inputs and discuss implications. Here results show that PV-with-battery designs are more profitable under our assumptions, but that designs including a concentrated solar power (CSP) system produce significantly greater annual energy; and that CSP-with-thermal energy storage designs maximizing the benefit-to-cost ratio have an input-dependent linear relationship between the CSP field solar multiple and the hours of storage as the project budget varies.

14 SOLAR ENERGY↗

Ground sculpting to enhance energy yield of vertical bifacial solar farms

The prospect of additional energy yield and improved reliability have increased commercial interest in bifacial solar modules. Recent publications have quantified the bifacial gain for several configurations. For example, a standalone, optimally-tilted bifacial panel placed over a flat ground (with 50% albedo) is expected to produce a bifacial energy gain of 30% (per module area). In contrast, self and mutual shading in a farm with periodically spaced panels reduces the bifacial gain to 10–15% (per farm area). Bifacial gain is negligible for vertical arrays—although the configuration is of significant interest since it can prevent soiling. Here, we calculate the bifacial gain of a solar farm where vertical arrays are placed over sculpted/patterned ground. We conclude that vertical panels straddling (upward) triangle-shaped ground maximizes the energy output. Our worldwide calculation with up-triangle ground configuration and 50% albedo leads to the following conclusion. Compared to a traditional tilted monofacial design, the bifacial gain is (i) small up to 20° latitude, (ii) increases to 50% at 40° latitude, and (iii) reaches up to 100% at 60° latitude. Overall, high bifacial gains are observed in many regions particularly those with moderate to low clearness index. The enhanced output, along with reduced soiling loss and lower cleaning cost of the ground sculpted vertical bifacial (GvBF) solar farm could be of significant technological interest, especially in regions such as the Middle East and North Africa (MENA) susceptible to significant soiling losses.

14 SOLAR ENERGY↗

Design study of wind turbines 50 kW to 3000 kW for electric utility applications: Analysis and design

In the conceptual design task, several feasible wind generator systems (WGS) configurations were evaluated, and the concept offering the lowest energy cost potential and minimum technical risk for utility applications was selected. In the optimization task, the selected concept was optimized utilizing a parametric computer program prepared for this purpose. In the preliminary design task, the optimized selected concept was designed and analyzed in detail. The utility requirements evaluation task examined the economic, operational, and institutional factors affecting the WGS in a utility environment, and provided additional guidance for the preliminary design effort. Results of the conceptual design task indicated that a rotor operating at constant speed, driving an AC generator through a gear transmission is the most cost effective WGS configuration. The optimization task results led to the selection of a 500 kW rating for the low power WGS and a 1500 kW rating for the high power WGS.

Source record↗

Best Practices for Wake Model and Optimization Algorithm Selection in Wind Farm Layout Optimization

This paper presents the results of two case studies regarding the wind farm layout optimization problem. We asked a general audience to take part in the studies that we designed, and nine individuals participated. Case study 1 considered variations in optimization strategies for a given simple Gaussian wake model. Participants were provided with a wake model that outputs annual energy production (AEP) for an input set of wind turbine locations. Participants used an optimization method of their choosing to find an optimal wind farm layout. Case study 2 looked at trade-offs in performance resulting from variation in both physics model and optimization strategy. For case study 2, participants calculated AEP using a wake model of their choice while also implementing their chosen optimization method. Participants then used their wake model to calculate the AEP all other participant submitted turbine configurations produce for cross-comparison results. for optimized turbine locations were then cross-compared by recalculating the AEP using every other participant's wake model. Results for case study 1 show that the best optimal wind farm layouts in this study were achieved by participants who used gradient-based optimization methods. A front-runner emerged with the Sparse Nonlinear OPTimizer plus Wake Expansion Continuation (SNOPTplusWEC) optimization method, which consistently discovered a higher AEP for each scenario. Results for case study 2 show that for small wind farms with few turbines, turbine placement on the wind farm boundary is superior. Conclusions for case study 2 were drawn from participant cross-comparison of results.

17 WIND ENERGY↗

Best Practices for Wake Model and Optimization Algorithm Selection in Wind Farm Layout Optimization: Preprint

This paper presents the results of two case studies regarding the wind farm layout optimization problem. We asked a general audience to take part in the studies that we designed, and nine individuals participated. Case study 1 considered variations in optimization strategies for a given simple Gaussian wake model. Participants were provided with a wake model that outputs annual energy production (AEP) for an input set of wind turbine locations. Participants used an optimization method of their choosing to find an optimal wind farm layout. Case study 2 looked at trade-offs in performance resulting from variation in both physics model and optimization strategy. For case study 2, participants calculated AEP using a wake model of their choice while also implementing their chosen optimization method. Participants then used their wake model to calculate the AEP all other participant submitted turbine configurations produce for cross-comparison results. for optimized turbine locations were then cross-compared by recalculating the AEP using every other participant's wake model. Results for case study 1 show that the best optimal wind farm layouts in this study were achieved by participants who used gradient-based optimization methods. A front-runner emerged with the Sparse Nonlinear OPTimizer plus Wake Expansion Continuation (SNOPTplusWEC) optimization method, which consistently discovered a higher AEP for each scenario. Results for case study 2 show that for small wind farms with few turbines, turbine placement on the wind farm boundary is superior. Conclusions for case study 2 were drawn from participant cross-comparison of results.

17 WIND ENERGY↗

A low temperature unitized regenerative fuel cell realizing 60% round trip efficiency and 10 000 cycles of durability for energy storage applications

Unitized regenerative fuel cells (URFC) convert electrical energy to and from chemical bonds in hydrogen. URFCs have the potential to provide economical means for efficient long-term, seasonal, energy storage and on-demand conversion back to electrical energy. We first optimize the catalyst layer for discrete electrolyzer and fuel cell and then configure the URFC. The goal is to identify a cost competitive configuration for URFCs, and demonstrate it in terms of upper limit of round trip efficiencies (RTEs). Two possible configurations of URFCs are compared via experiments and techno-economic analysis (TEA), which emphasize the advantages of the unconventional constant-electrode (CE) URFC over the traditional constant-gas (CG) configuration. We also study the stability via accelerated stress tests (ASTs) and demonstrate steady state operation in a daily cycle for day to night energy shifting. From the investigations, the optimum composition of the URFC anode catalyst layer is 90 at% Ir-black balanced by Pt-black for both CE and CG configurations. At 80 °C and 1 A cm -2 , the optimized CE URFC achieves 57% and 60% RTE with air and O 2 as the reductant gases, respectively. We then evaluated the differences in durability using an AST over 10k charge–discharge cycles; the results reveal that the wider potential window at the anode in CE (0.05–1.55 V) has minimal effect on catalyst layer stability compared to CG (0.55–1.55 V). Furthermore, there was no degradation up to the range of 2k–5k cycles; beyond that the fuel cell (discharge) performance degraded while the electrolyzer (charge) performance was still stable. Finally, the observations here indicate substantial potential to employ URFCs as efficient and cost-effective bidirectional energy-conversion devices within energy storage and utilization systems after appropriate technological and operational optimizations.

25 ENERGY STORAGE↗

Some optimal considerations in attitude control systems

The conventional six-engine reaction control jet relay attitude control law with deadband is shown to be a good linear approximation to a weighted time-fuel optimal control law. Techniques for evaluating the value of the relative weighting between time and fuel for a particular relay control law is studied along with techniques to interrelate other parameters for the two control laws. Vehicle attitude control laws employing control moment gyros are then investigated. Steering laws obtained from the expression for the reaction torque of the gyro configuration are compared to a total optimal attitude control law that is derived from optimal linear regulator theory. This total optimal attitude control law has computational disadvantages in the solving of the matrix Riccati equation. Several computational algorithms for solving the matrix Riccati equation are investigated with respect to accuracy, computational storage requirements, and computational speed.

Boland, J. S., III↗

Guidance and Control strategies for aerospace vehicles

A neighboring optimal guidance scheme was devised for a nonlinear dynamic system with stochastic inputs and perfect measurements as applicable to fuel optimal control of an aeroassisted orbital transfer vehicle. For the deterministic nonlinear dynamic system describing the atmospheric maneuver, a nominal trajectory was determined. Then, a neighboring, optimal guidance scheme was obtained for open loop and closed loop control configurations. Taking modelling uncertainties into account, a linear, stochastic, neighboring optimal guidance scheme was devised. Finally, the optimal trajectory was approximated as the sum of the deterministic nominal trajectory and the stochastic neighboring optimal solution. Numerical results are presented for a typical vehicle. A fuel-optimal control problem in aeroassisted noncoplanar orbital transfer is also addressed. The equations of motion for the atmospheric maneuver are nonlinear and the optimal (nominal) trajectory and control are obtained. In order to follow the nominal trajectory under actual conditions, a neighboring optimum guidance scheme is designed using linear quadratic regulator theory for onboard real-time implementation. One of the state variables is used as the independent variable in reference to the time. The weighting matrices in the performance index are chosen by a combination of a heuristic method and an optimal modal approach. The necessary feedback control law is obtained in order to minimize the deviations from the nominal conditions.

Hibey, J. L.↗

Automatic Aircraft Structural Topology Generation for Multidisciplinary Optimization and Weight Estimation

An approach is proposed for the application of rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process. This should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. A demonstration of this process is shown for two sample aircraft wing designs.

Sensmeier, Mark D.↗

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗

Recent advances in stellarator optimization

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. Here, we outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—was written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. Thus, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also discussed. A new algorithm developed for the design of the scraper element on W7-X is presented along with ideas for automating the optimization approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal feed flow sequence for multi-effect distillation system integrated with supercritical carbon dioxide Brayton cycle for seawater desalination

Multi-effect distillation is often integrated with a Rankine power cycle for cogeneration (simultaneous production of power and desalinated water). Such integration increases the condenser operating pressure for the Rankine cycle (and increases the heat-rejection temperature) to produce desalinated water, resulting in decreased power-plant efficiency. The supercritical carbon dioxide Brayton cycle has a higher efficiency compared to the Rankine cycle. The waste heat rejected from supercritical carbon dioxide Brayton cycle is at sufficiently hot temperature to have feasible energy integration with multi-effect distillation system. The paper introduces the novel concept of cogeneration without being a parasitic load to the power cycle. For the illustrative example considered, integrating 4-effect distillation system with a 115 MWe power plant can produce 3041 m3 of distillate per day at 1.06 $/m3, at a constant power plant efficiency of 49.2%. The pattern in which feed enters the desalination system often dictates its energy consumption. The two most commonly used feed configurations for multi-effect distillation system are parallel/cross feed and forward feed. With steam as a heat source (i.e., a latent heat source), parallel/cross feed is the most energy-efficient feed configuration. The other objective of this paper is to identify the optimal feed flow configuration for multi-effect distillation system integrated with a supercritical carbon dioxide power cycle (i.e., a sensible heat source). For the simplified network, forward feed is the best feed configuration, which yields a 7.5% increase in distillate production at 2.6% reduced distillate cost. Additionally, different methods for reducing the brine discharge are studied, which can help to achieve zero liquid discharge. Result show increasing the maximum brine concentration gives superior results compared to brine recycling. The system modelling is done using the principle of process integration, and an analytical methodology for cogeneration is derived.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗