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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 505 records · Page 28

Dynamic analysis of a photovoltaic power system with battery storage capability

A photovolataic power system with a battery storage capability is analyzed. A dual battery current control concept is proposed, which enables the battery to either supply or accept power depending upon system environment and load conditions. A simulation of the power system, including the battery current control, is developed and evaluated. The evaulation demonstrate the visbility of the battery control concept of switch the battery from a charge to discharge mode and back as required by load and environmental conditions. An acceptable system operation is demonstrated over the entire insolation range. Additionally, system sensitivity, bandwidth, and damping characteristics of the battery control are shown to be acceptable for a projected hardware implementation.

Merrill, W. C.↗

Approximation of Failure Probability Using Conditional Sampling

In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.

Giesy. Daniel P.↗

Finite Element Model Characterization Of Nano-Composite Thermal And Environmental Barrier Coatings

Thermal and environmental barrier coatings have been applied for protecting Si based ceramic matrix composite components from high temperature environment in advanced gas turbine engines. It has been found that the delamination and lifetime of T/EBC systems generally depend on the initiation and propagation of surface cracks induced by the axial mechanical load in addition to severe thermal loads. In order to prevent T/EBC systems from surface cracking and subsequent delamination due to mechanical and thermal stresses, T/EBC systems reinforced with nano-composite architectures have showed promise to improve mechanical properties and provide a potential crack shielding mechanism such as crack bridging. In this study, a finite element model (FEM) was established to understand the potential beneficial effects of nano-composites systems such as SiC nanotube-reinforced oxide T/EBC systems.

Yamada, Yoshiki↗

Orbital Eccentricity and the Stability of Planets in the Alpha Centauri System

Planets on initially circular orbits are typically more dynamically stable than planets initially having nonzero eccentricities. However, the presence of a major perturber that forces periodic oscillations of planetary eccentricity can alter this situation. We investigate the dependance of system lifetime on initial eccentricity for planets orbiting one star within the alpha Centauri system. Our results show that initial conditions chosen to minimize free eccentricity can substantially increase stability compared to planets on circular orbits.

Alpha Centauri System↗

Quasi-Wireless Capacitive Power Transfer with Secure Data Acquisition for Robotic Systems in Space Infrastructure

Space exploration is dependent on robotic systems that utilize end-effectors to collect samples, probe surfaces, and manipulate objects. These systems can rarely be designed to do all three, forcing engineers to make tradeoffs based on the mission parameters - i.e. should the robotic appendage have a claw, drill, or shovel, and which would be best suited for the mission? Additionally, as more industrial and government entities partake in space exploration, data protection is needed in transit and at rest. To address these challenges, we present a first-of-its- kind robotic linkage that has no wiring between the joints. Instead, quasi-wireless capacitive (QWiC) power transfer is used to send energy over the robot’s chassis without a return wire. This enables the system to be completely modular through the use of single-contact permanent magnet connections, allowing rapid alterations in joint kinematics and/or the changing of end-effectors. For collecting sensor data from the robotic arm and to send remote commands to it, we use a Supervisory Control and Data Acquisition (SCADA) system. Data transmission relies on MQTT and OPC UA communication protocols with encryption. The SCADA server logs and archives sensor data and provides the functionality for authorized users to send remote commands from SCADA client(s) to motors. A SCADA client can be any of the web browsers that connects to a server via a secure communication channel using SSL protocol. Furthermore, as an extra data protection mechanism, we inject noise to the sensor data traffic, which obfuscates the timing of sensor data packets and adds confusion about which data packet represents which motor.

wireless sensor networks↗

Postdisaster Routing of Movable Energy Resources for Enhanced Distribution System Resilience: A Deep Reinforcement Learning-Based Approach

The deployment of movable energy resources (MERs) can be an effective strategy to restore critical loads to enhance power system resilience when no other energy sources are available after the occurrence of an extreme event. Since the optimal locations of MERs following an extreme event are dependent on system operating states (e.g., the loads at each node, on/off status of system branches, and so on), existing analytical and population-based approaches must repeat the entire analysis and calculation when the system operating states change. On the contrary, if deep reinforcement learning (DRL)-based algorithms are sufficiently trained with a wide range of scenarios, they can quickly find optimal or near-optimal locations irrespective of changes in system states. A deep Q-learning-based approach is proposed for optimal MER deployment to enhance power system resilience. MERs can be also utilized to complement other types of resources, if available. The proposed approach operates in two stages after the occurrence of extreme events. In the first stage, the distribution network is represented as a graph, and the network is then reconfigured using tie switches by using Kruskal’s spanning forest search algorithm (KSFSA). To maximize critical load recovery, the optimal or near-optimal locations of MERs are chosen in the second stage. Further, case studies on a 33-node distribution system and a modified IEEE 123-node system demonstrate the effectiveness of the proposed approach for postdisaster routing of MERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Gamma-Ray Focusing Optics for Small Animal Imaging

There is a well-established need for high-resolution radionuclide imaging techniques that provide non-invasive measurement of physiological function in small animals. We, therefore, have begun developing a small animal radionuclide imaging system using grazing incidence mirrors to focus low-energy gamma-rays emitted by I-125, and other radionuclides. Our initial prototype optic, fabricated from thermally-formed glass, demonstrated a resolution of 1500 microns, consistent with the performance predicted by detailed simulations. More recently, we have begun constructing mirrors using a replication technique that reduces low spatial frequency errors in the mirror surface, greatly improving the resolution. Each technique offers particular advantages: e.g., multilayer coatings are easily deposited on glass, while superior resolution is possible with replicated optics. Scaling the results from our prototype optics, which only have a few nested shells, to system where the lens has a full complement of several tens of nested shells, a sensitivity of approx. 1 cps/micro Ci is possible, with the exact number dependent on system magnification and radionuclide species. (Higher levels of efficiency can be obtained with multi-optic imaging systems.) The gamma-ray lens will achieve a resolution as good as 100 microns, independent of the final sensitivity. The combination of high spatial resolution and modest sensitivity will enable in vivo single photon emission imaging studies in small animals.

Pivovaroff, M. J.↗

Determination of the Meteor Limiting Magnitude

The limiting meteor magnitude of a meteor camera system will depend on the camera hardware and software, sky conditions, and the location of the meteor radiant. Some of these factors are constants for a given meteor camera system, but many change between meteor shower or sporadic source and on both long and short timescales. Since the limiting meteor magnitude ultimately gets used to calculate the limiting meteor mass for a given data set, it is important to have an understanding of these factors and to monitor how they change throughout the night, as a 0.5 magnitude uncertainty in limiting magnitude translates to a uncertainty in limiting mass by a factor of two.

Kingery, A.↗

Configuration Management Process Assessment Strategy

Purpose: To propose a strategy for assessing the development and effectiveness of configuration management systems within Programs, Projects, and Design Activities performed by technical organizations and their supporting development contractors. Scope: Various entities CM Systems will be assessed dependent on Project Scope (DDT&E), Support Services and Acquisition Agreements. Approach: Model based structured against assessing organizations CM requirements including best practices maturity criteria. The model is tailored to the entity being assessed dependent on their CM system. The assessment approach provides objective feedback to Engineering and Project Management of the observed CM system maturity state versus the ideal state of the configuration management processes and outcomes(system). center dot Identifies strengths and risks versus audit gotcha's (findings/observations). center dot Used "recursively and iteratively" throughout program lifecycle at select points of need. (Typical assessments timing is Post PDR/Post CDR) center dot Ideal state criteria and maturity targets are reviewed with the assessed entity prior to an assessment (Tailoring) and is dependent on the assessed phase of the CM system. center dot Supports exit success criteria for Preliminary and Critical Design Reviews. center dot Gives a comprehensive CM system assessment which ultimately supports configuration verification activities.*

Henry, Thad↗

Data storage technology: Hardware and software, Appendix B

This project involves the development of more economical ways of integrating and interfacing new storage devices and data processing programs into a computer system. It involves developing interface standards and a software/hardware architecture which will make it possible to develop machine independent devices and programs. These will interface with the machine dependent operating systems of particular computers. The development project will not be to develop the software which would ordinarily be the responsibility of the manufacturer to supply, but to develop the standards with which that software is expected to confirm in providing an interface with the user or storage system.

Sable, J. D.↗

A time-dependent dusty gas dynamic model of axisymmetric cometary jets

The present time-dependent, axisymmetric dusty gas dynamical model of inner cometary atmospheres solves the coupled and time-dependent equations of continuity, momentum, and energy for a gas-dust mixture between the surface of the nucleus and 100 km, using an axisymmetric 40 x 40 grid structure. A novel numerical method employing a second-order accurate Godunov-type scheme with dimensional splitting is used to solve the time-dependent pde system. It is established that a subsolar dust spike not predicted by previous calculations is generated by narrow axisymmetric jets, together with a jet cone whose opening angle depends on the jet length.

Korosmezey, A.↗

Beamed microwave power transmission and its application to space

The general principles and special components of beamed microwave power transmission systems are outlined and their application to the space program are discussed. The beamed system is defined as starting with a dc source of power at the transmitting end, converting it to a microwave beam for transmission through space, and ending with the dc power output at the receiving end. An experimentally measured and certified dc-to-dc efficiency of 54 percent has been achieved, using this definition. The application discussed is that of a LEO to GEO transportation system that depends upon vehicles propelled by electric thrusters whose power is supplied by a microwave beam originating at the earth's surface. The advantages of the all-electronic system over a chemically propelled system are enumerated. The principles of space propulsion, particularly as they relate to electric propulsion, are outlined. Key components of the system and environmental considerations are discussed.

Brown, William C.↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

Efficient simulation of open quantum systems coupled to a reservoir through multiple channels

It is challenging to simulate open quantum systems that are connected to a reservoir through multiple channels. For example, vibrations may induce fluctuations in both energy gaps and electronic couplings, which represent two independent channels of system–bath couplings. Systems of this kind are ubiquitous in the processes of excited state radiationless decay. Combined with density matrix renormalization group (DMRG) and matrix product states (MPS) methods, we develop an interaction-picture chain mapping strategy for vibrational reservoirs to simulate the dynamics of these open systems, resulting in time-dependent spatially local system–bath couplings in the chain-mapped Hamiltonian. This transformation causes the entanglement generated by the system–bath interactions to be restricted within a narrow frequency window of vibrational modes, enabling efficient DMRG/MPS dynamical simulations. We demonstrate the utility of this approach by simulating singlet fission dynamics using a generalized spin-boson Hamiltonian with both diagonal and off-diagonal system–bath couplings. This approach generalizes an earlier interaction-picture chain mapping scheme, allowing for efficient and exact simulation of systems with multi-channel system–bath couplings using matrix product states, which may further our understanding of nonlocal exciton–phonon couplings in exciton transport and the non-Condon effect in energy and electron transfer.

Chemistry↗

Building partnerships for development of sustainable energy systems with atmospheric measurements

Atmospheric dynamics often play a critical role in the sustainability and reliability of diverse forms of energy production. This is especially true for the growing number of renewable energy deployments that harness aspects of the environment for power production. While the University of Memphis has a strong research background in energy systems, we have little experience working with the Earth and Environmental Systems Science Division (EESSD) and their associated User Facilities. Of particular interest to us is the Atmospheric Science Research and the Atmospheric Radiation Measurement (ARM) user facility to address surface-boundary layer interactions and physical phenomena. One of the major challenges for understanding and developing energy systems and management platforms is accurate modeling/forecasting of atmospheric conditions across disparate spatial and temporal scales. These conditions are often required to understand the lowest levels of the atmospheric boundary layer, but are also important to understand higher atmospheric conditions where aerosols affect cloud development. The objective of this work was to develop partnerships with national laboratories for collaboration on environmental science and its intersection with sustainable energy systems, as well as to leverage the ARM user facility data repositories to enhance our research capabilities in energy systems and their inter-dependence on environmental systems for future engagement with EESSD. Specifically, we accomplished these objectives by (1) developing collaborations with Oakridge National Laboratory ARM Data Science and Integration Group which resulted in student internships, (2) employed ARM data to develope modeling of the atmospheric boundary layer optical turbulence, and (3) optimally-sized large-scale renewable energy systems and their associated energy storage systems with ARM repository data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Continuation of research into software for space operations support: Conversion of the display manager to X Windows/Motif, volume 2

NASA is currently using a set of applications called the Display Builder and Display Manager. They run on Concurrent systems and heavily depend on the Graphic Kernel System (GKS). At this time however, these two applications would more appropriately be developed in X Windows, in which a low X is used for all actual text and graphics display and a standard widget set (such as Motif) is used for the user interface. Use of the X Windows will increase performance, improve the user interface, enhance portability, and improve reliability. Prototype of X Window/Motif based Display Manager provides the following advantages over a GKS based application: improved performance by using a low level X Windows, display of graphic and text will be more efficient; improved user interface by using Motif; Improved portability by operating on both Concurrent and Sun workstations; and Improved reliability.

Collier, Mark D.↗

Brief History of Agricultural Systems Modeling

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the next generation models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

agricultural systems↗

Hawaii Threat Brief

The Digital Energy Transformation is redefining how power systems operate, integrating physical infrastructure with digital technologies to enhance efficiency, visibility, and resilience. For islanded and digitally modernizing systems like Hawai‘i’s, this shift presents both new opportunities and evolving challenges in cybersecurity, supply chain assurance, and environmental resilience. This brief provides an overview of critical infrastructure dependencies and systemic risks associated with increasing digital integration. It summarizes recent energy-sector threat activity and case studies that illustrate adversary tactics and supply chain vulnerabilities, and identifies pathways to strengthen resilience.

25 - ENERGY STORAGE↗