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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 523 records · Page 29

Enhancing approximate modular Bayesian inference by emulating the conditional posterior

In modular Bayesian analyses, complex models are composed of distinct modules, each representing different aspects of the data or prior information. In this context, fully Bayesian approaches can sometimes lead to undesirable feedback between modules, compromising the integrity of the inference. The “cut-distribution” prevents unwanted influence between modules by “cutting” feedback. The direct sampling (DS) algorithm is standard practice for approximating the cut-distribution, but it can be computationally intensive, especially when the number of imputations required is large. An enhanced method is proposed, the Emulating the Conditional Posterior (ECP) algorithm, which leverages emulation to increase the number of imputations. Through numerical experiment it is demonstrated that the ECP algorithm outperforms the traditional DS approach in terms of accuracy and computational efficiency, particularly when resources are constrained. Here, it is also shown how the DS algorithm can be improved using ideas from design of experiments. Some practical recommendations are given for algorithm choice in modular Bayesian analyses.

97 MATHEMATICS AND COMPUTING↗

Space processing applications payload equipment study. Volume 2B: Payload interface analysis (power/thermal/electromagnetic compatibility)

As a part of the task of performing preliminary engineering analysis of modular payload subelement/host vehicle interfaces, a subsystem interface analysis was performed to establish the integrity of the modular approach to the equipment design and integration. Salient areas that were selected for analysis were power and power conditioning, heat rejection and electromagnetic capability (EMC). The equipment and load profiles for twelve representative experiments were identified. Two of the twelve experiments were chosen as being representative of the group and have been described in greater detail to illustrate the evaluations used in the analysis. The shuttle orbiter will provide electrical power from its three fuel cells in support of the orbiter and the Spacelab operations. One of the three shuttle orbiter fuel cells will be dedicated to the Spacelab electrical power requirements during normal shuttle operation. This power supplies the Spacelab subsystems and the excess will be available to the payload. The current Spacelab sybsystem requirements result in a payload allocation of 4.0 to 4.8 kW average (24 hour/day) and 9.0 kW peak for 15 minutes.

Hammel, R. L.↗

Electronic control of redox reactions inside Escherichia coli using a genetic module

Microorganisms regulate the redox state of different biomolecules to precisely control biological processes. These processes can be modulated by electrochemically coupling intracellular biomolecules to an external electrode, but current approaches afford only limited control and specificity. Here we describe specific electrochemical control of the reduction of intracellular biomolecules in Escherichia coli through introduction of a heterologous electron transfer pathway. E . coli expressing cymAmtrCAB from Shewanella oneidensis MR-1 consumed electrons directly from a cathode when fumarate or nitrate, both intracellular electron acceptors, were present. The fumarate-triggered current consumption occurred only when fumarate reductase was present, indicating all the electrons passed through this enzyme. Moreover, CymAMtrCAB-expressing E . coli used current to stoichiometrically reduce nitrate. Thus, our work introduces a modular genetic tool to reduce a specific intracellular redox molecule with an electrode, opening the possibility of electronically controlling biological processes such as biosynthesis and growth in any microorganism.

59 BASIC BIOLOGICAL SCIENCES↗

Modular machine learning-based elastoplasticity: Generalization in the context of limited data

The development of highly accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions and from the viewpoint of data availability, verification, and validation. Recently, data-driven modeling approaches have been proposed that aim to establish stress-evolution laws that avoid user-chosen functional forms by relying on machine learning representations and algorithms. However, these approaches not only require a significant amount of data but also need data that probes the full stress space with a variety of complex loading paths. Furthermore, they rarely enforce all necessary thermodynamic principles as hard constraints. Hence, they are in particular not suitable for low-data or limited-data regimes, where the first arises from the cost of obtaining the data and the latter from the experimental limitations of obtaining labeled data, which is commonly the case in engineering applications. In this work, we discuss a hybrid framework that can work on a variable amount of data by relying on the modularity of the elastoplasticity formulation where each component of the model can be chosen to be either a classical phenomenological or a data-driven model depending on the amount of available information and the complexity of the response. The method is tested on synthetic uniaxial data coming from simulations as well as cyclic experimental data for structural materials. The discovered material models are found to not only interpolate well but also allow for accurate extrapolation in a thermodynamically consistent manner far outside the domain of the training data. This ability to extrapolate from limited data was the main reason for the early and continued success of phenomenological models and the main shortcoming in machine learning-enabled constitutive modeling approaches. Training aspects and details of the implementation of these models into Finite Element simulations are discussed and analyzed.

42 ENGINEERING↗

Dynamic Contingency Analysis Tool 2.0 User Manual with Test System Examples

This document introduces Version 2 of the Dynamic Contingency Analysis Tool (DCAT) software package developed by Pacific Northwest National Laboratory and serves as a guide for using this package to conduct cascading failure simulations for the electric power system. The DCAT is an open-platform and publicly available software; it is intended to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will support finding mitigating actions to reduce the risk of cascading outages in technically sound and effective ways. This manual provides detailed instructions on how to use this tool on multicore Windows workstations or servers. In the public version of DCAT, several improvements have been made over the previous version: (1) it was modularized; (2) a graphical user interface (GUI) was developed; (3) a new version of the MPjobs parallel processing module was incorporated; and (4) a batch-processing function was added. The features of the DCAT GUI are described, including some examples of how to use the GUI to perform simulations. A full explanation of the DCAT methodology is available in the Phase 1 report.

24 POWER TRANSMISSION AND DISTRIBUTION↗

LANDSAT-D flight segment operations manual, volume 1

Hardware, systems, and subsystems for the multimission modular spacecraft used for LANDSAT 4 are described and depicted in block diagrams and schematics. Components discussed include the modular attitude control system; the communication and data handling subsystem; the narrowband tape recorder; the on-board computer; the propulsion module subsystem; the signal conditioning and control unit; the modular power subsystem; the solar array drive and power transmission assembly; the power distribution unit; the digital processing unit; and the wideband communication subsystem.

Varhola, J.↗

Developement of an Optimum Interpolation Analysis Method for the CYBER 205

A state-of-the-art technique to assimilate the diverse observational database obtained during FGGE, and thus create initial conditions for numerical forecasts is described. The GLA optimum interpolation (OI) analysis method analyzes pressure, winds, and temperature at sea level, mixing ratio at six mandatory pressure levels up to 300 mb, and heights and winds at twelve levels up to 50 mb. Conversion to the CYBER 205 required a major re-write of the Amdahl OI code to take advantage of the CYBER vector processing capabilities. Structured programming methods were used to write the programs and this has resulted in a modular, understandable code. Among the contributors to the increased speed of the CYBER code are a vectorized covariance-calculation routine, an extremely fast matrix equation solver, and an innovative data search and sort technique.

Nestler, M. S.↗

Advanced Support Equipment For Remote Experiments

Advanced Carrier Customer Equipment Support System (ACCESS) is system of electronic communication and data-processing equipment for controlling remote scientific instruments and monitoring readings of instruments via telemetry. Designed to incorporate modular hardware and software making it adapable to other uses (including terrestrial ones) with minimal modifications.

Lui, Ben Y.↗

Concepts to Automate Fluid Transfer Capability of Low Impact Docking System (LIDS)

The capability to transfer mass between spacecraft is necessary for many mission scenarios. Docking and berthing operations have enabled fluid, electrical, crew and equipment transfers to some degree on all manned space operations since the Gemini program. The Apollo program performed some sophisticated docking maneuvers to land men on the moon and return them safely to Earth. These programs primarily transferred crew, equipment, and pressurized atmosphere between docked spacecraft. The International Space Station (ISS) U.S. modules are connected by Common Berthing Mechanism (CBM) portals. They provide many feed-through ports for electrical, and fluid transfer between modules, as well as a large diameter crew and equipment tunnel. Fluid and electrical jumpers are manually installed after the CBM sealing surfaces have been securely mated to maintain the pressurized cabin environment. CBM berthing and subsequent fluid transfer capability requires a lengthy manual process involving an active interface that mates with a passive half. The Androgynous Peripheral Attach System (MAS) a Russian technology that docked the Russian Zarya module to Unity, or Node 1, is a more complex system that also is capable of fuel transfer, enabling refueling of the Russian re-boost engines on ISS. For several years, a Low Impact Docking System (LIDS) has been under development at Johnson Space Center (JSC). This docking technology has a requirement to be androgynous in order to allow the fabrication of a single configuration that can dock with all other LIDS units. It is desired to make electrical and fluid coupling mating an automated process to enable routine docking and undocking operations to support future exploration missions. It is envisioned that modular design and vehicle assembly will require an efficient LIDS for fuel, electrical, crew, and equipment transfer. Marshall Space Flight Center (MSFC) has joined the LIDS development effort and plans to employ fluid transfer concepts and technology from previous development programs, such as the Automated Fluid Interface System (AFIS) and the Ohital Fluid Transfer System (OFTS) that were developed and tested by MSFC. Orbital Expressderived robotic satellite servicing technology is scheduled to fly soon to demonstrate fluid transfer technology developed for the Air Force. This paper will compare known technology against possible fluid transfer requirements for LIDS to develop design strategies for automated fluid transfer.

Miernik, Janie H.↗

Avionics System Architecture for the NASA Orion Vehicle

It has been 30 years since the National Aeronautics and Space Administration (NASA) last developed a crewed spacecraft capable of launch, on-orbit operations, and landing. During that time, aerospace avionics technologies have greatly advanced in capability, and these technologies have enabled integrated avionics architectures for aerospace applications. The inception of NASA s Orion Crew Exploration Vehicle (CEV) spacecraft offers the opportunity to leverage the latest integrated avionics technologies into crewed space vehicle architecture. The outstanding question is to what extent to implement these advances in avionics while still meeting the unique crewed spaceflight requirements for safety, reliability and maintainability. Historically, aircraft and spacecraft have very similar avionics requirements. Both aircraft and spacecraft must have high reliability. They also must have as much computing power as possible and provide low latency between user control and effecter response while minimizing weight, volume, and power. However, there are several key differences between aircraft and spacecraft avionics. Typically, the overall spacecraft operational time is much shorter than aircraft operation time, but the typical mission time (and hence, the time between preventive maintenance) is longer for a spacecraft than an aircraft. Also, the radiation environment is typically more severe for spacecraft than aircraft. A "loss of mission" scenario (i.e. - the mission is not a success, but there are no casualties) arguably has a greater impact on a multi-million dollar spaceflight mission than a typical commercial flight. Such differences need to be weighted when determining if an aircraft-like integrated modular avionics (IMA) system is suitable for a crewed spacecraft. This paper will explore the preliminary design process of the Orion vehicle avionics system by first identifying the Orion driving requirements and the difference between Orion requirements and those of other previous crewed spacecraft avionics systems. Common systems engineering methods will be used to evaluate the value propositions, or the factors that weight most heavily in design consideration, of Orion and other aerospace systems. Then, the current Orion avionics architecture will be presented and evaluated.

Baggerman, Clint↗

Development of a Twin-spool Turbofan Engine Simulation Using the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3 of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

thermodynamic simulation↗

Development of a Twin-Spool Turbofan Engine Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3% of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

numerical simulation↗

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗

Additively Manufactured Solid-State Luminaire

This project addresses several key barriers to wide-spread adoption of additive manufacturing (AM) technology as applied to solid state lighting luminaires. The solution will utilize cutting edge AM approaches for integrating structure with thermal management solutions, electronic functionality, and optics. The research team (Eaton, Lighting Research Center (LRC) at Rensselaer Polytechnic Institute, Xerox Research Centre of Canada (XRCC)) utilize their AM and lighting expertise to investigate breakthrough manufacturing approaches that will significantly reduce cost, eliminate manufacturing process waste, and improve luminaire efficacy. The team has identified critical areas of research and proposed novel technical approaches to achieve these goals. Key areas of focus in Budget Period 1 (BP1) of the project quantified the impact of applying AM methodologies to the main, discrete subsystem components (Heat Sink, Housing, Optics, Electronics). Budget Period 2 (BP2) research explored similar impact on a fully integrated, AM modular luminaire concept. Final Achievement of the Target Metrics for the project are as follows: Material Reduction: achieved > 57.45% (target is 50%) Manufacturing Process: achieved > 51% reduction (target is 50%) Application Efficacy: achieved 126 lm/W (target is 130 lm/W) First Cost vs Baseline: demonstrated 49% improvement in project timing, 59% improvement in man hour savings and 89% worse BOM costs (due to deficiencies in current “state of the art” equipment). The BOM costs improve to 53% savings if state of the art processes and equipment could have been used.

3D Printing↗

Reusing Information Management Services for Recommended Decadal Study Missions to Facilitate Aerosol and Cloud Studies

NASA Earth Sciences Division (ESD) has made great investments in the development and maintenance of data management systems and information technologies, to maximize the use of NASA generated Earth science data. With information management system infrastructure in place, mature and operational, very small delta costs are required to fully support data archival, processing, and data support services required by the recommended Decadal Study missions. This presentation describes the services and capabilities of the Goddard Space Flight Center (GSFC) Earth Sciences Data and Information Services Center (GES DISC) and the reusability for these future missions. The GES DISC has developed a series of modular, reusable data management components currently in use. They include data archive and distribution (Simple, Scalable, Script-based, Science [S4] Product Archive aka S4PA), data processing (S4 Processor for Measurements aka S4PM), data search (Mirador), data browse, visualization, and analysis (Giovanni), and data mining services. Information management system components are based on atmospheric scientist inputs. Large development and maintenance cost savings can be realized through their reuse in future missions.

Kempler, Steve↗

Autonomous Operations for Advanced Reactors Utilizing Supervisory Control

Automation is a critical tenet of reactor plant operations as reliance on nuclear energy increases. Nuclear power plants require a large workforce which does not scale with output; that is, the cost per megawatt increases as reactor output becomes smaller. The economic viability of advanced reactors, particularly small modular reactors (SMRs) and microreactors, requires a significantly reduced onsite workforce. The logical solution is establishing a systematic process of elimination of reliance on human operators, and to the extent possible, replacing these actions with automated functions. In this paper, we propose a method for such transformation to establish a robust technical basis to enable transition to autonomy. Our method is based on finite state automata (FSA)—also known as finite state machines (FSMs). Relying on this method allows us to exploit the rich set of mathematical proofs available in the field of regular languages. FSA are one of the mathematical tools to model discrete event systems (DES). These properties are applied to produce an automated startup controller for the Massachusetts Institute of Technology Research Reactor (MITR). The startup procedure is captured in terms of discrete changes from one state to another while an independent supervisory control system directs the sequence of states and alerts a human in the event of an abnormal operation. First, the design and behavior of the MITR rod control system were modeled in Simulink. Then, the startup procedure was applied to the rod control system and the DES performed a startup by procedurally withdrawing rods to the subcritical position. The simulation also stops rod motion in response to an uncontrollable event and restarts rod motion once the event has been cleared.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Integrated structural-aerodynamic design optimization

This paper focuses on the processes of simultaneous aerodynamic and structural wing design as a prototype for design integration, with emphasis on the major difficulty associated with multidisciplinary design optimization processes, their enormous computational costs. Methods are presented for reducing this computational burden through the development of efficient methods for cross-sensitivity calculations and the implementation of approximate optimization procedures. Utilizing a modular sensitivity analysis approach, it is shown that the sensitivities can be computed without the expensive calculation of the derivatives of the aerodynamic influence coefficient matrix, and the derivatives of the structural flexibility matrix. The same process is used to efficiently evaluate the sensitivities of the wing divergence constraint, which should be particularly useful, not only in problems of complete integrated aircraft design, but also in aeroelastic tailoring applications.

Haftka, R. T.↗

A high fidelity and user-friendly equation-oriented optimization model for carbon capture using a novel water-lean solvent

Research Triangle Institute (RTI) International and SLB have developed a novel water-lean solvent technology for carbon capture, demonstrating low specific reboiler duty (SRD) values at capture rates exceeding 90%. At the Technology Centre Mongstad (TCM) pilot plant, the technology achieved an SRD of 2.55 GJ/t-CO2 at 95% capture, utilizing an intercooler and a 5°C temperature approach in the lean/rich solvent cross exchanger. To meet varying carbon capture targets for Front End Engineering and Design (FEED) studies and to enable real-time optimization and advanced process control, an efficient optimization model is required. This model needs to minimize energy demand for a given capture rate and determine optimal operating parameters in response to fluctuating flue gas conditions. While an existing Aspen Plus simulation model, developed by RTI and SLB, accurately matches TCM plant data, its sequential modular (SM) strategy is too slow for real-time applications due to recycle streams and tight heat integration inherent in solvent-based carbon capture processes. Although an equation-oriented (EO) modeling strategy is more suitable for optimizing these processes, its adoption has been limited by several factors: feature limitations in Aspen Plus EO mode (e.g., lack of balance block support), a less user-friendly interface for variable identification and loop solving, complex troubleshooting of convergence issues, and the necessity for accurate initial values.

carbon capture↗