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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Study of advanced composite structural design concepts for an arrow wing supersonic cruise configuration, task 3

A structural design study was conducted to assess the relative merits of structural concepts using advanced composite materials for an advanced supersonic aircraft cruising at Mach 2.7. The configuration and structural arrangement developed during Task I and II of the study, was used as the baseline configuration. Allowable stresses and strains were established for boron and advanced graphite fibers based on projected fiber properties available in the next decade. Structural concepts were designed and analyzed using graphite polyimide and boron polyimide, applied to stiffened panels and conventional sandwich panels. The conventional sandwich panels were selected as the structural concept to be used on the wing structure. The upper and lower surface panels of the Task I arrow wing were redesigned using high-strength graphite polyimide sandwich panels over the titanium spars and ribs. The ATLAS computer system was used as the basis for stress analysis and resizing the surface panels using the loads from the Task II study, without adjustment for change in aeroelastic deformation. The flutter analysis indicated a decrease in the flutter speed compared to the baseline titanium wing design. The flutter analysis indicated a decrease in the flutter speed compared to the baseline titanium wing design. The flutter speed was increased to that of the titanium wing, with a weight penalty less than that of the metallic airplane.

Source record↗
DOE OSTI2026

Integrating AI Data Centers with the Power Grid

The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying new tariff designs, including voluntary interruptible service riders, mandated flexibility requirements, and streamlined interconnection processes for flexible loads. For the highly capitalized and rapidly growing AI industry, the primary motivators for embracing these strategies are expediting facility interconnection, satisfying emerging regulatory mandates, and mitigating community resistance. While demand flexibility cannot substitute the long-term need for new bulk power generation, it serves as an essential, immediate solution for enabling near-term deployment. By transforming data centers from grid stressors into stabilizing assets, flexible operations can ensure reliable grid integration, ease market pressures, and support a resilient power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1988

Dynamically allocating sets of fine-grained processors to running computations

Researchers explore an approach to using general purpose parallel computers which involves mapping hardware resources onto computations instead of mapping computations onto hardware. Problems such as processor allocation, task scheduling and load balancing, which have traditionally proven to be challenging, change significantly under this approach and may become amenable to new attacks. Researchers describe the implementation of this approach used by the FFP Machine whose computation and communication resources are repeatedly partitioned into disjoint groups that match the needs of available tasks from moment to moment. Several consequences of this system are examined.

Middleton, David↗
NASA NTRS2016

Evidence Report: Risk of Performance Errors Due to Training Deficiencies

Substantial evidence supports the claim that inadequate training leads to performance errors. Barshi and Loukopoulos (2012) demonstrate that even a task as carefully developed and refined over many years as operating an aircraft can be significantly improved by a systematic analysis, followed by improved procedures and improved training (see also Loukopoulos, Dismukes, & Barshi, 2009a). Unfortunately, such a systematic analysis of training needs rarely occurs during the preliminary design phase, when modifications are most feasible. Training is often seen as a way to compensate for deficiencies in task and system design, which in turn increases the training load. As a result, task performance often suffers, and with it, the operators suffer and so does the mission. On the other hand, effective training can indeed compensate for such design deficiencies, and can even go beyond to compensate for failures of our imagination to anticipate all that might be needed when we send our crew members to go where no one else has gone before. Much of the research literature on training is motivated by current training practices aimed at current training needs. Although there is some experience with operations in extreme environments on Earth, there is no experience with long-duration space missions where crews must practice semi-autonomous operations, where ground support must accommodate significant communication delays, and where so little is known about the environment. Thus, we must develop robust methodologies and tools to prepare our crews for the unknown. The research necessary to support such an endeavor does not currently exist, but existing research does reveal general challenges that are relevant to long-duration, high-autonomy missions. The evidence presented here describes issues related to the risk of performance errors due to training deficiencies. Contributing factors regarding training deficiencies may pertain to organizational process and training programs for spaceflight, such as when training programs are inadequate or unavailable. Furthermore, failure to match between tasks on the one hand, and learning and memory abilities on the other hand is a contributing factor, especially when individuals' relative efficiency with which new information is acquired, and adjustments made in behavior or thinking, are inconsistent with mission demands. Thus, if training deficiencies are present, the likelihood of errors or of the inability to successfully complete a task increases. What's more, the overall risk to the crew, the vehicle, and the mission increases.

Barshi, Immanuel↗
NASA NTRS2019

Human Factors Applications of Biomechanical Modeling

Biomechanical data collection and modeling has applications to the field of human factors. Specifically, motion data can be used to determine the operational volume necessary for performing a task. The operational volume assessment can be performed in order to determine how much volume is needed to perform the task or if task performance can be contained and adequately performed within an allocated volume. Motion and external force data, along with computational modeling techniques, can be used to estimate the internal loading produced during performance of a task. Internal loading estimates can be used to determine if an adequate stimulus is generated for maintenance of musculoskeletal health and also for comparison to injury thresholds to determine injury risk during task performance.

Lewandowski, Beth↗
DOE OSTI2023

Usage Pattern Analysis for the Summit Login Nodes

High performance computing (HPC) users interact with Summit through dedicated gateways, also known as login nodes. The performance and stability of these login nodes can have a significant impact on the user experience. In this study, the performance and stability of Summit’s five login nodes are evaluated by analyzing the log data from 2020 and 2021. The analysis focuses on the computing capability (CPU average load, users and tasks) and the storage performance, along with the associated job scheduler activity. The outcome of this study can serve as the foundation of a predictive modeling framework that enables the system admin of an HPC system to preemptively deploy countermeasures before the onset of a system failure.

Eiffert, Brett↗
DOE OSTI2025

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1983

Cryogenic Fluid Management Experiment (CFME) trunnion verification testing

The Cryogenic Fluid Management Experiment (CFME) was designed to characterize subcritical liquid hydrogen storage and expulsion in the low-g space environment. The CFME has now become the storage and supply tank for the Cryogenic Fluid Management Facility, which includes transfer line and receiver tanks, as well. The liquid hydrogen storage and supply vessel is supported within a vacuum jacket to two fiberglass/epoxy composite trunnions which were analyzed and designed. Analysis using the limited available data indicated the trunnion was the most fatigue critical component in the storage vessel. Before committing the complete storage tank assembly to environmental testing, an experimental assessment was performed to verify the capability of the trunnion design to withstand expected vibration and loading conditions. Three tasks were conducted to evaluate trunnion integrity. The first determined the fatigue properties of the trunnion composite laminate materials. Tests at both ambient and liquid hydrogen temperatures showed composite material fatigue properties far in excess of those expected. Next, an assessment of the adequacy of the trunnion designs was performed (based on the tested material properties).

Bailey, W. J.↗
NASA NTRS1994

M.E.366-J embodiment design project: Portable foot restraint

During space shuttle operations, astronauts require support to carry out tasks in the weightless environment. In the past, portable foot restraints (PFR) with orientations adjustable in pitch, roll, and yaw provided this support for payload bay operations. These foot restraints, however, were designed for specific tasks with a load limit of 111.2 Newtons. Since the original design, new applications for foot restraints have been identified. New designs for the foot restraints have been created to boost the operational work load to 444.8 Newtons and decrease setup times. What remains to be designed is an interface between the restraint system and the extravehicular mobility unit (EMU) boots. NASA provided a proposed locking device involving a spring-loaded mechanism. This locking mechanism must withstand loads of 1334.4 Newtons in any direction and weigh less than 222.4 Newtons. This paper develops an embodiment design for the interface between the PFR and the EMU boots. This involves design of the locking mechanism and a removable cleat that allows the boot to interface with this mechanism. The design team used the Paul Beitz engineering methodology to present the systematic development, structural analysis, and production considerations of the embodiment design. This methodology provides a basis for understanding the justification behind the decisions made in the design.

Heaton, Randall↗
NASA NTRS1994

Triton 2 (1B)

The goal of this project was to perform a detailed design analysis on a conceptually designed preliminary flight trainer. The Triton 2 (1B) must meet the current regulations in FAR Part 23. The detailed design process included the tasks of sizing load carrying members, pulleys, bolts, rivets, and fuselage skin for the safety cage, empennage, and control systems. In addition to the regulations in FAR Part 23, the detail design had to meet established minimums for environmental operating conditions and material corrosion resistance.

Clark, Michelle L.↗
NASA NTRS2011

Loft: An Automated Mesh Generator for Stiffened Shell Aerospace Vehicles

Loft is an automated mesh generation code that is designed for aerospace vehicle structures. From user input, Loft generates meshes for wings, noses, tanks, fuselage sections, thrust structures, and so on. As a mesh is generated, each element is assigned properties to mark the part of the vehicle with which it is associated. This property assignment is an extremely powerful feature that enables detailed analysis tasks, such as load application and structural sizing. This report is presented in two parts. The first part is an overview of the code and its applications. The modeling approach that was used to create the finite element meshes is described. Several applications of the code are demonstrated, including a Next Generation Launch Technology (NGLT) wing-sizing study, a lunar lander stage study, a launch vehicle shroud shape study, and a two-stage-to-orbit (TSTO) orbiter. Part two of the report is the program user manual. The manual includes in-depth tutorials and a complete command reference.

Eldred, Lloyd B.↗
NASA NTRS2023

Loft: An Automated Mesh Generator for Stiffened-Shell Aerospace Vehicles

Loft is an automated mesh generation code designed for aerospace vehicle structures. Based on user input, it can generate meshes for wings, noses, tanks, fuselage sections, thrust structures, etc. As the mesh is generated, each element is assigned properties that mark what part of the vehicle it is associated with. This property assignment is an extremely powerful feature making possible detailed analysis tasks such as load application and sizing. Loft can save its meshes in NASTRAN bulk data deck, EDS’ I-DEAS Universal File format, Abaqus input file format, VRML 2.0 (Virtual Reality Modeling Language) and STL (Stereo Lithography) files. The property assignment scheme was designed to make sizing in Collier Research’s HyperSizer easy. Support for other mesh storage formats can be added as needed.

Structural modeling↗
DOE OSTI2023

BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]

The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings. BuildingsBench is a platform for: - Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database. - Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF. We provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.

Emami, Patrick↗
NASA NTRS1993

Loads produced by a suited subject performing tool tasks without the use of foot restraints

With an increase in the frequency of extravehicular activities (EVA's) aboard the Space Shuttle, NASA is interested in determining the capabilities of suited astronauts while performing manual tasks during an EVA, in particular the situations in which portable foot restraints are not used to stabilize the astronauts. Efforts were made to document the forces that are transmitted to spacecraft while pushing and pulling an object as well as while operating a standard wrench and an automatic power tool. The six subjects studied aboard the KC-135 reduced gravity aircraft were asked to exert a maximum torque and to maintain a constant level of torque with a wrench, to push and pull an EVA handrail, and to operate a Hubble Space Telescope (HST) power tool. The results give an estimate of the forces and moments that an operator will transmit to the handrail as well as to the supporting structure. In general, it was more effective to use the tool inwardly toward the body rather than away from the body. There were no differences in terms of strength capabilities between right and left hands. The power tool was difficult to use. It is suggested that ergonomic redesigning of the power tool may increase the efficiency of power tool use.

Rajulu, Sudhakar L.↗
NASA NTRS1988

Mental workload dynamics in adaptive interface design

In examining the role of time in mental workload, the authors present a different perspective from which to view the problem of assessment. Mental workload is plotted in three dimensions, whose axes represent effective time for action, perceived distance from desired goal state, level of effort required to achieve the time-constrained goal. This representation allows the generation of isodynamic workload contours that incorporate the factors of operator skill and equifinality of effort. An adaptive interface for dynamic task reallocation is described that uses this form of assessment to reconcile the joint aims of stable operator loading and acceptable primary task performance by the total system.

Hancock, Peter A.↗
DOE OSTI2021

Piston Bowl Geometry Effects on Gasoline Compression Ignition in a Heavy-Duty Diesel Engine

A design optimization campaign was conducted to search for improved combustion profiles that enhance gasoline compression ignition in a heavy-duty diesel engine with a geometric compression ratio of 17.3. A large-scale design of experiments approach was used for the optimization, employing three-dimensional computational fluid dynamics simulations. The main parameters explored include geometric features, injector specifications, and swirl motion. Both stepped-lip and re-entrant bowls were included in order to assess their respective performance implications. A total of 256 design candidates were prepared using the software package CAESES for automated and simultaneous geometry generation and combustion recipe perturbation. The design optimization was conducted for three engine loads representing light to medium load conditions. The design candidates were evaluated for fuel efficiency, emissions, fuel-air mixing, and global combustion behavior. Simulation results showed that the optimum designs were all stepped-lip bowls, due to improvements in fuel-air mixing, as well as reduced heat loss and emissions formation. Improvements in indicated specific fuel consumption of up to 3.2% were achieved while meeting engine-out NOx emission targets of 1-1.5 g/kW center dot h. Re-entrant bowls performed worse compared to the baseline design, and significant performance variations occurred across the load points. Specifically, the re-entrant bowls were on par with the stepped-lip bowls under light load conditions, but significant deteriorations occurred under higher load conditions. As a final task, selected optimized designs were then evaluated under full-load conditions.

CFD↗