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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 757 records · Page 42

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Clukey, Steven J.↗

Electromagnetic characterization of conformal antennas

The ultimate objective of this project is to develop a new technique which permits an accurate simulation of microstrip patch antennas or arrays with various feed, superstrate and/or substrate configurations residing in a recessed cavity whose aperture is planar, cylindrical or otherwise conformed to the substructure. The technique combines the finite element and boundary integral methods to formulate a system suitable for solution via the conjugate gradient method in conjunction with the fast Fourier transform. The final code is intended to compute both scattering and radiation patterns of the structure with an affordable memory demand. With upgraded capabilities, the four included papers examined the radar cross section (RCS), input impedance, gain, and resonant frequency of several rectangular configurations using different loading and substrate/superstrate configurations.

Volakis, John L.↗

A new technology perspective and engineering tools approach for large, complex and distributed mission and safety critical systems components

Rapidly emerging technology and methodologies have out-paced the systems development processes' ability to use them effectively, if at all. At the same time, the tools used to build systems are becoming obsolescent themselves as a consequence of the same technology lag that plagues systems development. The net result is that systems development activities have not been able to take advantage of available technology and have become equally dependent on aging and ineffective computer-aided engineering tools. New methods and tools approaches are essential if the demands of non-stop and Mission and Safety Critical (MASC) components are to be met.

Carrio, Miguel A., Jr.↗

An overview of the current state of the art optimization used for trajectory design in the GTS system

The high cost of delivering payloads to orbit demands that launch vehicles be flown in an optimal and reliable manner. Thus, computer simulated trajectories are optimized to obtain maximum vehicle payload capability or a maximum amount of reserve fuel, subject to design constraints. The Generalized Trajectory Simulation (GTS) system developed at The Aerospace Corporation is capable of simulating and optimizing trajectories for a wide variety of boost and reentry problems. Optimization is an integral part of the GTS system. This has resulted in progressive use of optimization. Additionally, the flexibility of the GTS system allows optimum trade studies to be conducted and complicated missions to be designed. This paper describes the integrated and flexible nature of the optimization software in the GTS system. Special features of the NLP2 and NLP3 optimization codes are described. Post optimality, parameter sensitivity analysis and the automatic scaling capability in the GTS system are also described.

Beltracchi, Todd J.↗

Confessions of a robot lobotomist

Since its inception, numerically controlled (NC) machining methods have been used throughout the aerospace industry to mill, drill, and turn complex shapes by sequentially stepping through motion programs. However, the recent demand for more precision, faster feeds, exotic sensors, and branching execution have existing computer numerical control (CNC) and distributed numerical control (DNC) systems running at maximum controller capacity. Typical disadvantages of current CNC's include fixed memory capacities, limited communication ports, and the use of multiple control languages. The need to tailor CNC's to meet specific applications, whether it be expanded memory, additional communications, or integrated vision, often requires replacing the original controller supplied with the commercial machine tool with a more powerful and capable system. This paper briefly describes the process and equipment requirements for new controllers and their evolutionary implementation in an aerospace environment. The process of controller retrofit with currently available machines is examined, along with several case studies and their computational and architectural implications.

Gottshall, R. Marc↗

Formal methods for life-critical software

The use of computer software in life-critical applications, such as for civil air transports, demands the use of rigorous formal mathematical verification procedures. This paper demonstrates how to apply formal methods to the development and verification of software by leading the reader step-by-step through requirements analysis, design, implementation, and verification of an electronic phone book application. The current maturity and limitations of formal methods tools and techniques are then discussed, and a number of examples of the successful use of formal methods by industry are cited.

Butler, Ricky W.↗

Air Traffic Control Technology

The steady growth in air travel will lead to heightened demands for additional airspace capacity, particularly in the vicinity of terminals. New computer-aided processing of aircraft and navigational capability exemplified by the Global Positioning System will allow more sophisticated management of air traffic. Additional altitudes and over-flight areas may be necessary to effectively use the newer technology,

Denery, Dallas↗

Formal Methods for Life-Critical Software

The use of computer software in life-critical applications, such as for civil air transports, demands the use of rigorous formal mathematical verification procedures. This paper demonstrates how to apply formal methods to the development and verification of software by leading the reader step-by-step through requirements analysis, design, implementation, and verification of an electronic phone book application. The current maturity and limitations of formal methods tools and techniques are then discussed, and a number of examples of the successful use of formal methods by industry are cited.

Butler, Ricky W.↗

Evolutionary Scheduler for the Deep Space Network

A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.

Guillaume, Alexandre↗

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

COSS Lesson Creation Process

COSS (Crew On-Orbit System Support) is changing. Designed as computer based in-flight refresher training, it is getting good reviews and the demands on the product can be expected to increase. Last year, the lessons were written using Authorware, which had a number of limitations. The most important one was that the navigation and the layout functions were both in one package that was not easy to learn. The lesson creator had to be good at both programming and design. There were also a number of other problems, as detailed in my report last year. This year the COSS unit made the switch to embrace modularity. The navigation function is handled by a player that was custom-written using Delphi. The layout pages are now standard HTML files that can be created using any number of products. This new system gives new flexibility and unties the process from one product (and one company). The player can be re-written by a programmer without affecting the lesson pages. It is also now possible for anybody with a word-processor to make part of the HTML lesson pages and to use many of the new commercially available tools that are being designed for web pages. This summer I created a computer-based training (CBT) lesson on the IBM ThinkPad 760 ED and 760XD laptop computers that should fly on the International Space Station. I also examined the COSS system, the new player and the other new software products.

Harper, R. Stephen↗

Evolving HPC and Application Design Toward a Coupled Data Assimilation System at NASA Suitable for Emerging Exascale Platforms

The prediction capabilities of global models have continuously evolved from the traditional medium-range global weather prediction application to span scales in support of hourly prediction of convective scale storms to seasonal Earth system prediction. This evolution has increased the demands on the system infrastructure design and workflow to achieve the required performance on modern high-performance computing (HPC) platforms. The planned evolution of the Goddard Earth Observing System (GEOS) modeling and assimilation system will stress the capabilities of conventional HPC overwhelming the available compute cycles at the NASA Center for Climate Simulation (NCCS) at the NASA Goddard Space Flight Center in the coming 5-10 years. This has led to the re-design of key elements of the assimilation and modeling systems to achieve significant gains in performance on anticipated Exacale platforms. The transition of the assimilation system to the Joint Effort for Data assimilation Integration (JEDI) framework has positioned GEOS to exploit new efficient algorithms for data assimilation (DA) in a fully-coupled Earth system context. The suitability of the GEOS model to leverage a domain specific language (DSL) approach and artificial intelligence (AI) is being explored to accelerate computational performance and data exchange efficiency of the coupled Earth system model. The storage and processing of large data volumes produced by these advance systems is being redesigned with a data-centric cloud-based approach. We will highlight the recent efforts in these areas and emphasize the demand for further development and re-design to achieve the science objectives in support of NASA's Earth system modeling and assimilation missions.

Putman, Bill↗

Decentralized Failure-Tolerant Optimization of Electric Vehicle Charging

We present a decentralized failure-tolerant algorithm for optimizing electric vehicle (EV) charging, using charging stations as computing agents. The algorithm is based on the alternating direction method of multipliers (ADMM) and it has the following features: (i) It handles capacity, peak demand, and ancillary services coupling constraints. (ii) It does not require a central agent collecting information and performing coordination (e.g. an aggregator), instead all agents exchange information and computations are carried out in a fully decentralized fashion. (iii) It can withstand the failure of any number of computing agents, as long as the remaining computing agents are in a connected communications network. We construct this algorithm by reformulating the optimal EV charging problem in a decomposable form, amenable to ADMM, and then developing efficient decentralized solution methods for the subproblems dealing with coupling constraints. We conduct numerical experiments on industry-scale synthetic EV charging datasets, with up to 1,152 charging stations, using a high performance computing cluster. The experiments demonstrate that the proposed algorithm can solve the optimal EV charging problem fast enough to permit the integration of EV charging with real-time electricity markets, even in the presence of failures.

42 ENGINEERING↗

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗

Accelerating Demand Paging for Local and Remote Out-of-Core Visualization

This paper describes a new algorithm that improves the performance of application-controlled demand paging for the out-of-core visualization of data sets that are on either local disks or disks on remote servers. The performance improvements come from better overlapping the computation with the page reading process, and by performing multiple page reads in parallel. The new algorithm can be applied to many different visualization algorithms since application-controlled demand paging is not specific to any visualization algorithm. The paper includes measurements that show that the new multi-threaded paging algorithm decreases the time needed to compute visualizations by one third when using one processor and reading data from local disk. The time needed when using one processor and reading data from remote disk decreased by up to 60%. Visualization runs using data from remote disk ran about as fast as ones using data from local disk because the remote runs were able to make use of the remote server's high performance disk array.

Ellsworth, David↗

The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era

Sensors, enabling observations across vast spatial, spectral, and temporal scales, are major data generators for information technology (IT). Processing, storing, and communicating this ever-growing amount of data pose challenges for the current IT infrastructure. Edge computing—an emerging paradigm to overcome the shortcomings of cloud-based computing—could address these challenges. Furthermore, emerging technologies such as quantum computing, quantum sensing, and quantum communications have the potential to fill the performance gaps left by their classical counterparts. Here, we present the concept of an edge quantum computing (EQC) simulator—a platform for designing the next generation of edge computing applications. An EQC simulator is envisioned to integrate elements from both quantum technologies and edge computing to allow studies of quantum edge applications. The presented concept is motivated by the increasing demand for more sensitive and precise sensors that can operate faster at lower power consumption, generating both larger and denser datasets. These demands may be fulfilled with edge quantum sensor networks. Envisioning the EQC era, we present our view on how such a scenario may be amenable to quantification and design. Given the cost and complexity of quantum systems, constructing physical prototypes to explore design and optimization spaces is not sustainable, necessitating EQC infrastructure and component simulators to aid in co-design. We discuss what such a simulator may entail and possible use cases that invoke quantum computing at the edge integrated with new sensor infrastructures.

47 OTHER INSTRUMENTATION↗

Dynamic regulation of erythropoiesis: A computer model of general applicability

A mathematical model for the control of erythropoiesis was developed based on the balance between oxygen supply and demand at a renal oxygen detector which controls erythropoietin release and red cell production. Feedback regulation of tissue oxygen tension is accomplished by adjustments of hemoglobin levels resulting from the output of a renal-bone marrow controller. Special consideration was given to the determinants of tissue oxygenation including evaluation of the influence of blood flow, capillary diffusivity, oxygen uptake and oxygen-hemoglobin affinity. A theoretical analysis of the overall control system is presented. Computer simulations of altitude hypoxia, red cell infusion hyperoxia, and homolytic anemia demonstrate validity of the model for general human application in health and disease.

Leonard, J. I.↗

helios: An R package to process heating and cooling degrees for GCAM

helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.

97 MATHEMATICS AND COMPUTING↗