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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Scalable Method for Decarbonizing Modular Building Solutions

The decarbonization movement emphasizes the shift in focus from energy efficiency to directly reducing global-warming impact. Blokable, LLC, a vertically integrated modular builder with an all-electric portfolio, worked with NREL on a roadmap to decarbonize its high-performance building product at a relative cost advantage by utilizing the learning curves of mass production. Previous decarbonization literature focused on either i) lifecycle assessments, or ii) efficiency measures. These decarbonization exercises were bespoke to individual building projects and did not consider positive feedback loops of builder experience or process repetition. Vertically integrated, prefab builders possess the unique ability to leverage learning and repetition to decarbonize their design-build-operate process. This collaboration between Blokable and NREL resulted in a decarbonization strategy utilizing the company's scaling and production efficiencies, on-site renewable energy and storage, and the projected evolution of building components over time based on trends and emerging legislation. The method developed here encompasses a growing business model, lifecycle carbon assessment, and projected changes in product and grid emissions over time due to existing trends and emerging legislation. This methodology incorporates learning-curve efficiencies gleaned from scaled manufacturing, as well as open-source tools integration for energy and carbon accounting. The output projects and compares cost and carbon savings per modular unit as production increases to 10,000 dwelling units annually over 15 years. The resulting roadmap illustrates a path to roughly 60% carbon savings and beyond-net-zero-energy performance at no incremental cost by 2030. The methodology can be mapped to other integrated or productized builders for methodical decarbonization.

affordable housing↗
DOE OSTI2025

Electrical signaling in fungi: past and present challenges

Abstract Electrical signaling is a fundamental mechanism for integrating environmental stimuli and coordinating responses in living organisms. While extensively studied in animals and plants, the role of electrical signaling in fungi remains a largely underexplored field. Early studies suggested that filamentous fungi generate action potential-like signals and electrical currents at hyphal tips, yet their function in intracellular communication remained unclear. Renewed interest in fungal electrical activity has fueled developments such as the hypothesis that mycorrhizal networks facilitate electrical communication between plants and the emerging field of fungal-based electronic materials. Given their continuous plasma membrane, specialized septal pores, and insulating cell wall structures, filamentous fungi possess architectural features that could support electrical signaling over long distances. However, studying electrical phenomena in fungal networks presents unique challenges due to the microscopic dimensions of hyphae, the structural complexity of highly modular mycelial networks, and the limitations of traditional electrophysiological methods. This review synthesizes current evidence for electrical signaling in filamentous fungi, evaluates methodological approaches, and highlights experimental challenges. By addressing these challenges and identifying best practices, we aim to advance research in this field and provide a foundation for future studies exploring the role of electrical signaling in fungal biology.

Buffi, Matteo↗
NASA NTRS1981

A programing system for research and applications in structural optimization

The paper describes a computer programming system designed to be used for methodology research as well as applications in structural optimization. The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities existing in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of contraints and design variables. Features shown in numerical examples include: (1) variability of structural layout and overall shape geometry, (2) static strength and stiffness constraints, (3) local buckling failure, and (4) vibration constraints. The paper concludes with a review of the further development trends of this programing system.

Sobieszczanski-Sobieski, J.↗
NASA NTRS2004

Transformational System Concepts and Technologies for Our Future in Space

Continued constrained budgets and growing national and international interests in the commercialization and development of space requires NASA to be constantly vigilant, to be creative, and to seize every opportunity for assuring the maximum return on space infrastructure investments. Accordingly, efforts are underway to forge new and innovative approaches to transform our space systems in the future to ultimately achieve two or three or five times as much with the same resources. This bold undertaking can be achieved only through extensive cooperative efforts throughout the aerospace community and truly effective planning to pursue advanced space system design concepts and high-risk/high-leverage research and technology. Definitive implementation strategies and roadmaps containing new methodologies and revolutionary approaches must be developed to economically accommodate the continued exploration and development of space. Transformation can be realized through modular design and stepping stone development. This approach involves sustainable budget levels and multi-purpose systems development of supporting capabilities that lead to a diverse amy of sustainable future space activities. Transformational design and development requires revolutionary advances by using modular designs and a planned, stepping stone development process. A modular approach to space systems potentially offers many improvements over traditional one-of-a-kind space systems comprised of different subsystem element with little standardization in interfaces or functionality. Modular systems must be more flexible, scaleable, reconfigurable, and evolvable. Costs can be reduced through learning curve effects and economies of scale, and by enabling servicing and repair that would not otherwise be feasible. This paper briefly discusses achieving a promising approach to transforming space systems planning and evolution into a meaningful stepping stone design, development, and implementation process. The success of this well planned and orchestrated approach holds great promise for achieving innovation and revolutionary technology development for supporting future exploration and development of space.

Howell, Joe T.↗
NASA NTRS1987

A multidomain global modeling technique for analysis of Space Shuttle main engine

A multidomain global modeling technique is presented. The purpose of this multidomain methodology is to simultaneously analyze the three-dimensional compressible flow field in Space Shuttle main engine components. This technique provides flexibility and modularity for individual domain and also simplifies the grid generation task for each domain. A two-way coupling procedure is adopted for exchanging interface boundary conditions. This algorithm which requires that the adjacent domains share an overlapping grid slab, is fully conservative and implicit. For non-matching grid systems and for non-overlapping interfaces, an interpolation and/or extrapolation procedure is used when transferring the interface boundary conditions at the adjacent domains. To maintain overall conservation, a flux correction method is subsequently used. The coupling procedure was verified by modeling several geometries with features similar to SSME components. Satisfactory results for all test cases were obtained. Finally, this algorithm has been applied to the SSME flow simulation.

Tam, L. T.↗
DOE OSTI2025

NE-COST plug-in: Expanding ACCERT's Capabilities for Life-Cycle Cost Modeling

The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.

Zhou, Jia↗
NASA NTRS1991

Formal and heuristic system decomposition methods in multidisciplinary synthesis

The multidisciplinary interactions which exist in large scale engineering design problems provide a unique set of difficulties. These difficulties are associated primarily with unwieldy numbers of design variables and constraints, and with the interdependencies of the discipline analysis modules. Such obstacles require design techniques which account for the inherent disciplinary couplings in the analyses and optimizations. The objective of this work was to develop an efficient holistic design synthesis methodology that takes advantage of the synergistic nature of integrated design. A general decomposition approach for optimization of large engineering systems is presented. The method is particularly applicable for multidisciplinary design problems which are characterized by closely coupled interactions among discipline analyses. The advantage of subsystem modularity allows for implementation of specialized methods for analysis and optimization, computational efficiency, and the ability to incorporate human intervention and decision making in the form of an expert systems capability. The resulting approach is not a method applicable to only a specific situation, but rather, a methodology which can be used for a large class of engineering design problems in which the system is non-hierarchic in nature.

Bloebaum, Christina L.↗
NASA NTRS1990

Test plan pressure fed thrust chamber technology

Aerojet is developing the technology for the design of a reliable, low cost, efficient, and lightweight LOX/RP-1 pressure fed engine. This technology program is a direct result of Aerojet's liquid rocket booster (LRB) study and previous NASA studies that identified liquid engines using high bulk density hydrocarbon fuels as very attractive for a space transportation system (STS). Previous large thrust LOX/RP-1 engine development programs were characterized by costly development problems due to combustion instability damage. The combustion stability solution was typically obtained through trial and error methods of minimizing instability damage by degrading engine performance. The approach to this program was to utilize existing and newly developed combustion analysis models and design methodology to create a thrust chamber design with features having the potential of producing reliable and efficient operation. This process resulted in an engine design with a unique high thrust-per-element OFO triplet injector utilizing a low cost modular approach. Cost efficient ablative materials are baselined for the injector face and chamber. Technology demonstration will be accomplished through a hot fire test program using appropriately sized subscale hardware. This subscale testing will provide a data base to supplement the current industry data bank and to anchor and validate the applied analysis models and design methodology. Once anchored and validated, these analysis models and design methodology can be applied with greatly increased confidence to design and characterize a large scale pressure fed LOX/RP-1 thrust chamber. The objective of this test program is to generate a data base that can be used to anchor and validate existing analysis models and design methodologies and to provide early concept demonstration of a low cost, efficient LOX/RP-1 thrust chamber. Test conditions and hardware instrumentation were defined to provide data sufficient to characterize combustion stability, performance, and thermal operation over a wide thrust chamber throttling range.

Dunn, Glenn↗
NASA NTRS1986

Towards a general object-oriented software development methodology

An object is an abstract software model of a problem domain entity. Objects are packages of both data and operations of that data (Goldberg 83, Booch 83). The Ada (tm) package construct is representative of this general notion of an object. Object-oriented design is the technique of using objects as the basic unit of modularity in systems design. The Software Engineering Laboratory at the Goddard Space Flight Center is currently involved in a pilot program to develop a flight dynamics simulator in Ada (approximately 40,000 statements) using object-oriented methods. Several authors have applied object-oriented concepts to Ada (e.g., Booch 83, Cherry 85). It was found that these methodologies are limited. As a result a more general approach was synthesized with allows a designer to apply powerful object-oriented principles to a wide range of applications and at all stages of design. An overview is provided of this approach. Further, how object-oriented design fits into the overall software life-cycle is considered.

Seidewitz, ED↗
NASA NTRS2019

An Automated Detection Methodology for Dry Well-Mixed Layers

The intense surface heating over arid land surfaces produces dry well-mixed layers (WML) via dry convection. These layers are characterized by nearly constant potential temperature and low, nearly constant water vapor mixing ratio. To further the study of dry WMLs, we created a detection methodology and supporting software to automate the identification and characterization of dry WMLs from multiple data sources including rawinsondes, remote sensing platforms, and model products. The software is a modular code written in Python, an open source language. Radiosondes from a network of synoptic stations in North Africa were used to develop and test the WML detection process. The detection involves an iterative decision tree that ingests a vertical profile from an input data file, performs a quality check for sufficient data density, and then searches upward through the column for successive points where the simultaneous changes in water vapor mixing ratio and potential temperature are less than the specified maxima. If points in the vertical profile meet the dry WML identification criteria, statistics are generated detailing the characteristics of each layer in the profile. At the end of the vertical profile analysis, there is an option to plot analyzed profiles in a variety of file formats. Initial results show that the detection methodology can be successfully applied across a wide variety of input data and North African environments and for all seasons. It is sensitive enough to identify dry WMLs from other types of isentropic phenomena such as subsidence layers and distinguish the current day’s dry WML from previous days.

Stephen D. Nicholls↗
NASA NTRS1981

Modular hardware synthesis using an HDL

Although hardware description languages (HDL) are becoming more and more necessary to automated design systems, their application is complicated due to the difficulty in translating the HDL description into an implementable format, nonfamiliarity of hardware designers with high-level language programming, nonuniform design methodologies and the time and costs involved in transfering HDL design software. Digital design language (DDL) suffers from all of the above problems and in addition can only by synthesized on a complete system and not on its subparts, making it unsuitable for synthesis using standard modules or prefabricated chips such as those required in LSI or VLSI circuits. The present paper presents a method by which the DDL translator can be made to generate modular equations that will allow the system to be synthesized as an interconnection of lower-level modules. The method involves the introduction of a new language construct called a Module which provides for the separate translation of all equations bounded by it.

Covington, J. A.↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
DOE OSTI2021

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↗
NASA NTRS1999

Standard Reference Rainfall Products Used in the TRMM Ground Efforts

The Primary goal of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) effort is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies. To this end, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County produces monthly rainfall accumulation reference products for each of the four primary TRMM GV sites. These products, standard methodology for deriving monthly, gauge-adjusted rainfall products, are utilized for each primary site. The monthly rainfall GV reference products are developed in discrete, modular steps with distinct intermediate products. These developmental steps, which will be fully discussed, include: (1) extracting radar data over locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z_R relationship from quality-controlled merged data over monthly time scales. A summary of all gauge statistics and GV rainfall reference products available for TRMM science users will be presented. Basic reference product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for primary GV site will be discussed. Finally, the sample impact on monthly rainfall reference products, through varying the time interval between intermediate rainfall accumulations, will be analyzed and presented.

Marks, David A.↗
DOE OSTI2022

Automatic Segmentation of Building Envelope Point Cloud Data Using Machine Learning

About 50% of buildings in the US were constructed before energy codes were introduced. Modular overclad panel retrofits, in which a new envelope is constructed over the existing building, are a promising solution given that it minimizes occupant disruption and shortens construction time at the jobsite. Current state-of-the-art retrofit panel layout and dimensioning consists of three steps: 1) 3D point cloud data generation of the building envelope using commonly available surveying equipment, 2) manual segmentation of 3D point cloud data by a trained professional to identify and dimension window openings, door openings, and other architectural features, and 3) modular panel layout optimization and dimensioning by an architect or engineer. Among these steps, the second one remains the most difficult and costly because it is very labor-intensive. We propose a methodology to automatically label 3D point cloud data to reduce the time and expense spent in manual segmentation. Machine learning methods were employed to classify the point cloud data into distinct groups, each of which corresponds to different features of the building envelope. After classification, a segmentation algorithm was developed to perform boundary detection and separate the components of the façade. Finally, the algorithm returns the relative positions and dimensions of the features in the building envelope. The measurements obtained with the proposed automated method were compared against the actual dimensions to determine the overall algorithm accuracy. The proposed algorithm can then be used to reduce manual efforts for 3D point cloud labeling before modular panel layout optimization is performed.

Maldonado Puente, Bryan↗
DOE OSTI2026

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗
NASA NTRSDate not supplied

Urban Air Mobility Traffic Analysis Tool for Airspace Involving Vertiport Hub Operations to Examine Simulated Conflicts

Presented herein are details of the development of an Urban Air Mobility Traffic Analysis Tool (UAM TAT), designed to analyze the traffic of Vertical Take-off and Landing (VTOL) air-craft in urban agglomerations to enable the Urban Air Mobility(UAM) operations. The tool aims to address challenges of UAM operations in a simulated airspace by testing different scenarios and methods for air traffic management. It emphasizes the need for effective risk management practices and methodologies to ensure the safety of operations, given the increasing use of highly automated aircraft (i.e., Advanced Air Mobility (AAM))in urban environments. The tool is modular and allows for the simulation of various families of VTOLs and different air traffic rules, making it suitable for defining and estimating airspace and vertiports capacity, determining VTOL requirements, and testing and comparing air traffic management methods. The results of five different simulations are presented that show the capabilities and functionalities of the tool. The simulations present the impact of vertiport hub operations and various ATM approach on the VTOLs’ conflicts.

Urban Air Mobility↗