Results for “Optimized Configurations” — Page 24

DOE OSTI2025

Assessing the Impact of Large Removable Beryllium Reflector Experiments on HFIR Performance and Safety Metrics

This study investigated the effect of various removable beryllium (RB) experiment configurations on High Flux Isotope Reactor (HFIR) metrics to address increasing interest in these facilities for materials and fuels irradiation research. The RB reflector contains eight large and four small irradiation experiment facilities that offer excellent neutron flux conditions to perform fission and fusion reactor materials and fuels irradiation research. This work aims to outline acceptable RB configurations based on safety, performance, and programmatic metrics. This study assessed experiment effects on reactivity, cycle length, fission rate density distributions, and neutron flux distributions using the Shift, HFIRCON, and SCALE ORIGEN codes. Initial evaluations focused on generic experiment materials including aluminum plugs, stainless steel plugs, molybdenum plugs, and aluminum plugs with gadolinium shields. Subsequent analyses of MiniFuel experiments were performed to evaluate a heterogenous experiment, consisting of a more complex geometry and bearing several materials, and to test the correlations developed with the generic materials on a real experiment. Furthermore, the effects of neutron poison concentrations in the standard beryllium plugs were evaluated. When assuming a reference RB configuration with eight large fresh beryllium plugs, perturbed configurations with three aluminum plugs, one stainless steel plug, one molybdenum plug, one gadolinium-shielded aluminum plug, and one MiniFuel experiment resulted in a cycle length reduction of less than 1.3 days, the current threshold before requiring additional approvals. Configurations with five aluminum plugs, one stainless steel plug, one molybdenum plug, one gadolinium-shielded aluminum plug, and two MiniFuel experiments meet the 1.3 day limit if irradiated beryllium plugs are considered. Fuel element fission rate density distributions remained within safety limits, with maximum local increases under 9%. Neutron flux calculations revealed large thermal flux depressions inside and around the perturbed RB facilities, while epithermal and fast neutron fluxes increased because of reduced neutron moderation by the perturbed materials. These findings provide valuable guidance for optimizing RB configurations to balance safety and performance at HFIR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2023

Modeling and Simulation of the Angel Upper Limb Offload Device: Branching Into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

NASA NTRS2023

Modeling and Simulation of The Angel Upper Limb Offload Device: Branching into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

DOE OSTI2021

A Laboratory Assessment and Optimization of Nanoparticle-Stabilized CO2 Foams for Hydraulic Fracturing Applications

In this research, we have conducted a comprehensive assessment and optimization of aqueous CO2 foams for fracturing applications. The performance of CO2 foams is evaluated using three major matrices: foam stability, foam apparent viscosity, and leakoff. The response of these performance matrices to different internal factors and external conditions is evaluated. These factors and conditions include foam quality, nanoparticle concentration, salinity, shear rate, surfactant type and concentration, polymer concentration, and temperature. Before foam generation, the colloidal stability of the nanosilica dispersion is evaluated at different types of electrolytes and under high temperatures. With a good salinity resistance and thermal stability, the nanosilica is then used for the entire set of foam generation experiments. The foam configuration with optimized parameters is used for the leakoff test, which serves as a supplementary section to further demonstrate the advantages of the proposed foam system. Then the final commercialization section provides a general view of what should be considered to commercialize the research results. In general, it is found that the aqueous CO2 foam system has demonstrated a good potential to be used as a fracturing fluid. The design of the foam system needs to consider formations properties and formation fluid properties etc. to realize the optimal performance of the system on a laboratory scale.

02 PETROLEUM↗

DOE OSTI2025

Secondary electron emission for reticulated carbon foam surfaces using direct measurements and spectroscopic analysis

This study investigates secondary electron emission (SEE) characteristics of reticulated foams using direct measurements and analytical modeling. Total SEE was quantified, revealing suppression of up to 44% in carbon foam structures compared to planar graphite surfaces. An optimal geometric configuration was identified and supported by analytical models. SEE angular dependence experiments showed diverse behaviors: fiber-like behavior and directional dependence for pore and ligaments on the mm scale, with fuzz-like characteristics when the foam features are between 10–100 µm. Electron energy analyzer measurements showed that carbon foams preferentially suppress inelastic backscattered electrons (BSEs) more so than true secondary electrons (SEs). The analysis indicated a larger fraction of low-energy SE generation in foams compared to flat surfaces due to increased emission from curved fiber ligaments and tertiary SEs from high-energy BSEs. These findings have implications for design and optimization of materials with tailored electron emission properties for applications like plasma-facing components, spacecraft materials, and accelerator surfaces.

Auger↗

DOE OSTI2022

NSTX-U theory, modeling and analysis results

Here, the mission of the low aspect ratio spherical tokamak NSTX-U is to advance the physics basis and technical solutions required for optimizing the configuration of next-step steady-state tokamak fusion devices. NSTX-U will ultimately operate at up to 2 MA of plasma current and 1 T toroidal field on axis for 5 s, and has available up to 15 MW of neutral beam injection power at different tangency radii and 6 MW of high harmonic fast wave heating. With these capabilities NSTX-U will develop the physics understanding and control tools to ramp-up and sustain high performance fully non-inductive plasmas with large bootstrap fraction and enhanced confinement enabled via the low aspect ratio, high beta configuration. With its unique capabilities, NSTX-U research also supports ITER and other critical fusion development needs. Super-Alfvénic ions in beam-heated NSTX-U plasmas access energetic particle (EP) parameter space that is relevant for both α-heated conventional and low aspect ratio burning plasmas. NSTX-U can also generate very large target heat fluxes to test conventional and innovative plasma exhaust and plasma facing component solutions. This paper summarizes recent analysis, theory and modelling progress to advance the tokamak physics basis in the areas of macrostability and 3D fields, EP stability and fast ion transport, thermal transport and pedestal structure, boundary and plasma material interaction, RF heating, scenario optimization and real-time control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2024

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗

NASA NTRS2021

Evaluation of Sensor Uncertainty Mitigation Methods for Detect-and-Avoid Systems

The impact of sensor noise on the performance of Detect-And-Avoid (DAA) systems can be reduced by implementing various mitigation schemes. This paper evaluates two such methods. One of them is the Sensor Uncertainty Mitigation (SUM) method, implemented in the Detect and Avoid Alerting Logic for Unmanned Systems (DAIDALUS) algorithm, a reference implementation in the DAA minimum operational performance standards. The second method is the Virtual Intruder State Aggregation (VISA), which averages multiple subsequent intruder states extrapolated to the current (most recent) time into a single ``aggregated`` intruder state. The VISA method can be used either individually as a sensor noise mitigation method in its own right, or in combination with DAIDALUS SUM. The performance of these methods is evaluated using three safety and operational suitability metrics and compared with a baseline configuration using static safety buffers. A large number of encounters representative of low-speed unmanned aircraft against non-cooperative manned aircraft, not equipped with a broadcasting transponder or ADS-B out system, are simulated and evaluated. An air-to-air radar model produces representative sensor noise for the DAA system. Results show that increasing the DAIDALUS SUM parameters for horizontal and vertical uncertainty improves the safety metric at the cost of increasing the number of actionable alerts leading to increased workload. A range of SUM parameters is recommended as suitable values for the type of operations considered for this work. VISA was found to be almost as effective as other noise mitigation methods even when it was used alone. Combining VISA with DAIDALUS SUM achieved the best performance among all investigated methods used with DAIDALUS. General trends and optimal SUM configurations were found to be nearly the same for two large and very different encounter data sets.

Detect-and-Avoid Systems↗

DOE OSTI2024

Two-Step Hyperparameter Optimization Method: Accelerating Hyperparameter Search by Using a Fraction of a Training Dataset

Abstract Hyperparameter optimization (HPO) is an important step in machine learning (ML) model development, but common practices are archaic—primarily relying on manual or grid searches. This is partly because adopting advanced HPO algorithms introduces added complexity to the workflow, leading to longer computation times. This poses a notable challenge to ML applications, as suboptimal hyperparameter selections curtail the potential of ML model performance, ultimately obstructing the full exploitation of ML techniques. In this article, we present a two-step HPO method as a strategic solution to curbing computational demands and wait times, gleaned from practical experiences in applied ML parameterization work. The initial phase involves a preliminary evaluation of hyperparameters on a small subset of the training dataset, followed by a reevaluation of the top-performing candidate models postretraining with the entire training dataset. This two-step HPO method is universally applicable across HPO search algorithms, and we argue it has attractive efficiency gains. As a case study, we present our recent application of the two-step HPO method to the development of neural network emulators for aerosol activation. Although our primary use case is a data-rich limit with many millions of samples, we also find that using up to 0.0025% of the data—a few thousand samples—in the initial step is sufficient to find optimal hyperparameter configurations from much more extensive sampling, achieving up to 135× speedup. The benefits of this method materialize through an assessment of hyperparameters and model performance, revealing the minimal model complexity required to achieve the best performance. The assortment of top-performing models harvested from the HPO process allows us to choose a high-performing model with a low inference cost for efficient use in global climate models (GCMs).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Feedback Power Cost Optimization in Power Distribution Networks with Prosumers

Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

System-Level Design Studies for Large Rotors

We examine the effect of rotor design choices on the power capture and structural loading of each major wind turbine component. A steady-state, harmonic model derived from simulations using the NREL aeroelastic code FAST is developed to reduce computational expense while evaluating design trade-offs for rotors with radii greater than 100 m. Design studies are performed, which focus on blade aerodynamic and structural parameters as well as different hub configurations and nacelle placements atop the tower. The effects of tower design and closed-loop control are also analyzed. Design loads are calculated according to the IEC design standards and used to calibrate the harmonic model and quantify uncertainty. Our design studies highlight both industry trends and innovative designs: we progress from a conventional, upwind, 3-bladed rotor, to a rotor with longer, more slender blades that is downwind and 2-bladed. For a 13 MW design, we show that increasing the blade length by 25 m while decreasing the induction factor of the rotor increases annual energy capture by 11% while constraining peak blade loads. A downwind, 2-bladed rotor design is analyzed, with a focus on its ability to reduce peak blade loads by 10% per 5 deg. of cone angle, and also reduce total blade mass. However, when compared to conventional, 3-bladed, upwind designs, the peak main bearing load of the up-scaled, downwind, 2-bladed rotor is increased by 280%. Optimized teeter configurations and individual pitch control can reduce non-rotating damage equivalent loads by 45% and 22%, respectively, compared with fixed-hub designs.

17 WIND ENERGY↗

DOE OSTI2022

Advanced Ceramic Membranes/Modules for Ultra Efficient Hydrogen (H2) Production/Carbon Dioxide (CO2) Capture for Coal-Based Polygeneration Plants: Fabrication, Testing, and CFD Modeling

Inorganic membrane-based systems are a promising technology for precombustion CO2 capture with simultaneous H2 production. State-of-the-art packages for high temperature and pressure service consist of multiple tube membrane bundles prepared in a "candle filter" configuration, in which the membrane tubes are open at one end and sealed at the other. This configuration is used for practical reasons, specifically the need to minimize problems due to thermal expansion mismatch between the ceramic tube bundle and the steel housing. However, the primary technical problem with the candle filter format for commercial-scale installations is the inability to purge the tube side (typically the permeate side), a feature that is crucial for high H2 recovery. In this study, the focus is to design and fabricate the first dual-end open full ceramic multiple tube membrane bundle that enables tube side (permeate) purge for gas separation applications. An additional key feature of this design is the simplified module layout, as the membrane bundles can be installed end-to-end with tube side (permeate) flow directly from one bundle to the next. This layout simplifies the membrane to housing seals and yields significant improvement in membrane packing density. Detailed focus areas in our studies include: (i) Materials development and preparation of the tube-to-tube sheet potting for the dual-ended bundle; (ii) the sealing and optimal module configuration design to minimize membrane stress upon module mounting; (iii) the demonstration, via the fabrication of CMS and Pd-alloy membranes supported on full-size, dual-ended ceramic support bundles, of the first example of a purgeable ceramic membrane and module; and (iv) development of a CFD model of the membrane module for calculation of feed flow distribution, and for use in scale-up, and capital cost estimating. The CFD model was validated using experimental data with the multi-tubular membrane system, employing He/N2 as a model gas mixture (surrogate for H2/CO2), and has been shown to be quite accurate. Employing the model, we are able to study the effects of operating pressure and temperature, feed and sweep gas flow rates, and the choice of membrane tube configuration on system performance.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Advanced Ceramic Membranes/Modules for Ultra Efficient Hydrogen (H2) Production/Carbon Dioxide (CO2) Capture for Coal-Based Polygeneration Plants: Fabrication, Testing and CFD Modeling

Inorganic membrane-based systems are a promising technology for precombustion CO2 capture with simultaneous H2 production. State-of-the-art packages for high temperature and pressure service consist of multiple tube membrane bundles prepared in a "candle filter" configuration, in which the membrane tubes are open at one end and sealed at the other. This configuration is used for practical reasons, specifically the need to minimize problems due to thermal expansion mismatch between the ceramic tube bundle and the steel housing. However, the primary technical problem with the candle filter format for commercial-scale installations is the inability to purge the tube side (typically the permeate side), a feature that is crucial for high H2 recovery. In this study, the focus is to design and fabricate the first dual-end open full ceramic multiple tube membrane bundle that enables tube side (permeate) purge for gas separation applications. An additional key feature of this design is the simplified module layout, as the membrane bundles can be installed end-to-end with tube side (permeate) flow directly from one bundle to the next. This layout simplifies the membrane to housing seals and yields significant improvement in membrane packing density. Detailed focus areas in our studies include: (i) Materials development and preparation of the tube-to-tube sheet potting for the dual-ended bundle; (ii) the sealing and optimal module configuration design to minimize membrane stress upon module mounting; (iii) the demonstration, via the fabrication of CMS and Pd-alloy membranes supported on full-size, dual-ended ceramic support bundles, of the first example of a purgeable ceramic membrane and module; and (iv) development of a CFD model of the membrane module for calculation of feed flow distribution, and for use in scale-up, and capital cost estimating. The CFD model was validated using experimental data with the multi-tubular membrane system, employing He/N2 as a model gas mixture (surrogate for H2/CO2), and has been shown to be quite accurate. Employing the model, we are able to study the effects of operating pressure and temperature, feed and sweep gas flow rates, and the choice of membrane tube configuration on system performance.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2019

System-level design studies for large rotors

Abstract. We examine the effect of rotor design choices on the power capture and structural loading of each major wind turbine component. A harmonic model for structural loading is derived from simulations using the National Renewable Energy Laboratory (NREL) aeroelastic code FAST to reduce computational expense while evaluating design trade-offs for rotors with radii greater than 100 m. Design studies are performed, which focus on blade aerodynamic and structural parameters as well as different hub configurations and nacelle placements atop the tower. The effects of tower design and closed-loop control are also analyzed. Design loads are calculated according to the IEC design standards and used to create a mapping from the harmonic model of the loads and quantify the uncertainty of the transformation. Our design studies highlight both industry trends and innovative designs: we progress from a conventional, upwind, three-bladed rotor to a rotor with longer, more slender blades that is downwind and two-bladed. For a 13 MW design, we show that increasing the blade length by 25 m, while decreasing the induction factor of the rotor, increases annual energy capture by 11 % while constraining peak blade loads. A downwind, two-bladed rotor design is analyzed, with a focus on its ability to reduce peak blade loads by 10 % per 5° of cone angle and also reduce total blade mass. However, when compared to conventional, three-bladed, upwind designs, the peak main-bearing load of the upscaled, downwind, two-bladed rotor is increased by 280 %. Optimized teeter configurations and individual pitch control can reduce non-rotating damage equivalent loads by 45 % and 22 %, respectively, compared with fixed-hub designs.

17 WIND ENERGY↗

NASA NTRS1994

Evaluation of NASA's end-to-end data systems using DSDS+

The Data Systems Dynamic Simulator (DSDS+) is a software tool being developed by the authors to evaluate candidate architectures for NASA's end-to-end data systems. Via modeling and simulation, we are able to quickly predict the performance characteristics of each architecture, to evaluate 'what-if' scenarios, and to perform sensitivity analyses. As such, we are using modeling and simulation to help NASA select the optimal system configuration, and to quantify the performance characteristics of this system prior to its delivery. This paper is divided into the following six sections: (1) The role of modeling and simulation in the systems engineering process. In this section, we briefly describe the different types of results obtained by modeling each phase of the systems engineering life cycle, from concept definition through operations and maintenance; (2) Recent applications of DSDS+. In this section, we describe ongoing applications of DSDS+ in support of the Earth Observing System (EOS), and we present some of the simulation results generated of candidate system designs. So far, we have modeled individual EOS subsystems (e.g. the Solid State Recorders used onboard the spacecraft), and we have also developed an integrated model of the EOS end-to-end data processing and data communications systems (from the payloads onboard to the principle investigator facilities on the ground); (3) Overview of DSDS+. In this section we define what a discrete-event model is, and how it works. The discussion is presented relative to the DSDS+ simulation tool that we have developed, including it's run-time optimization algorithms that enables DSDS+ to execute substantially faster than comparable discrete-event simulation tools; (4) Summary. In this section, we summarize our findings and 'lessons learned' during the development and application of DSDS+ to model NASA's data systems; (5) Further Information; and (6) Acknowledgements.

Rouff, Christopher↗

DOE OSTI2024

Flow field design for zero-gap microbial electrolysis cells using synthetic and real wastewater

Increasing performance in microbial electrolysis cells (MECs) requires the development of optimized reactor configurations with minimal internal resistance and capable to operate with real wastewater. Here, the impact of two different flow fields (serpentine and circular) was examined in zero-gap MECs with synthetic and real wastewaters. The serpentine flow field enabled a uniform distribution of the electrolyte in the anode chamber, resulting in larger current densities at lower flow rates compared to the circular flow field. Electrochemical tests using synthetic media with high buffer capacity revealed more stable and higher performance with the serpentine flow field compared to the circular flow path, producing larger current density (23.7 ± 0.8 A/m 2 vs 21.9 ± 5.6 A/m 2 ), hydrogen production rate (75.8 ± 4.1 L/L-d vs 54.3 ± 2.4 L/L-d), cathodic coulombic efficiency (>91 % vs >50 %), and an overall lower internal resistance (12.5 ± 0.5 mΩm 2 vs 14.8 ± 3.7 mΩm 2 ). Continuous operation for over 30 days with real wastewater indicated higher tolerance of the MECs with serpentine flow field toward media with large concentration of suspended solids, producing a current density of 5.4 ± 1.1 A/m 2 and a hydrogen production rate of 22.2 ± 6.2 L/L-d. Furthermore, the results presented here underscore the importance of reactor design and architecture in optimizing MEC performance for hydrogen production from liquid wastes.

flow path↗

DOE OSTI2022

Optimizing detachment control using the magnetic configuration of divertors

Abstract As tokamak research moves to reactor conditions, the control of a stable, optimally-detached divertor plasma has become increasingly relevant. Simple predictions of such detachment control have been performed previously using the detachment location sensitivity (DLS) model (Lipschultz et al 2016 Nucl. Fusion 56 056007). In this study the DLS model is extended and combined with SOLPS-ITER simulations of isolated divertor grids to study the effects of alternate divertor magnetic field properties on detachment control. The DLS model predicts that divertors can achieve easier access to detachment through a long connection length, a high total flux expansion, and a high average magnetic field in the divertor compared with that at the x -point. SOLPS-ITER simulations suggest an even stronger impact of total flux expansion and connection length on detachment access than the DLS model predicts. In terms of detachment evolution, both simulation and modelling show a high gradient in the total magnetic field and low B p o l B are able to more easily keep a detachment front at a desired poloidal location. Regions with no stable detachment front locations can arise for high magnetic field gradients directed towards the target. Significant differences have been found between impurity scan simulations and the DLS model. These differences may be attributed to sources and sinks of power and electron pressure, and should be explored further in future work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗