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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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DOE OSTI2024

Scalable and Highly-Efficient Microbial Electrochemical Reactor for Hydrogen Generation from Wastes

The overall goal of this project was to develop a scalable and highly efficient hybrid microbial electrochemical reactor for hydrogen recovery from waste streams at a cost of less than $\$$2/kg H₂. The specific objectives were: (1) to design and fabricate a scalable and highly efficient microbial electrochemical cell (MEC) reactor, and (2) to determine the techno-economic feasibility of the system for H₂ generation from organic-rich waste streams. We achieved the first objective by (a) developing low-cost electrode materials, (b) synthesizing a highly efficient cathode catalyst in a scalable manner, (c) evaluating and validating the developed electrode material and catalyst in MEC reactors, and (d) designing and fabricating a larger reactor that incorporates (a) to (c). We met the second objective by (a) identifying the impacts of wastewater composition and operational conditions on H₂ production, and (b) developing a cost-performance model that identified critical parameters affecting the system's performance and cost, providing a pathway for further improvement.

08 HYDROGEN↗

DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model

Inspired by recent advancements of simulating periodic systems on quantum computers, we develop a new approach, (SC)$^2$-ADAPT-VQE, to further advance the simulation of these systems. Our approach extends the scalable circuits ADAPT-VQE framework, which builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable ``Surrogate Constructed'' method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined. Bringing together the scalable circuits and the surrogate constructed approaches forms the core of the (SC)$^2$ methodology. Our approach allows for a wider set of classical computations, on small volumes, which can be used for a more robust extrapolation protocol. While developed in the context of lattice models, the surrogate construction portion is applicable to a wide variety of problems where information about the relative importance of operators in the pool is available. As an example, we use it to compute properties of the Schwinger model - quantum electrodynamics for a single, massive fermion in $1+1$ dimensions - and show that our method can be used to accurately extrapolate to the continuum limit.

Gustafson, Erik [RIACS, Mtn. View] (ORCID:00000001↗

NASA NTRS1987

Energy-absorption capability and scalability of square cross section composite tube specimens

Static crushing tests were conducted on graphite/epoxy and Kevlar/epoxy square cross section tubes to study the influence of specimen geometry on the energy-absorption capability and scalability of composite materials. The tube inside width-to-wall thickness (W/t) ratio was determined to significantly affect the energy-absorption capability of composite materials. As W/t ratio decreases, the energy-absorption capability increases nonlinearly. The energy-absorption capability of Kevlar epoxy tubes was found to be geometrically scalable, but the energy-absorption capability of graphite/epoxy tubes was not geometrically scalable.

Farley, Gary L.↗

NASA NTRS1989

Energy-absorption capability and scalability of square cross section composite tube specimens

Farley, Gary L.↗

NASA NTRS1994

Automated Scalability Analysis Tools for Message Passing Parallel Programs

In order to develop scalable parallel applications, a number of programming decisions have to be made during the development of the program. Performance tools that help in making these decisions are few, if existent. Traditionally, performance tools have focused on exposing performance bottlenecks of small-scale executions of the program. However, it is common knowledge that programs that perform exceptionally well on small processor configurations, more often than not, perform poorly when executed on larger processor configurations. Hence, new tools that predict the execution characteristics of scaled-up programs are an essential part of an application developers toolkit. In this paper we discuss important issues that need to be considered in order to build useful scalability analysis tools for parallel programs. We introduce a simple tool that automatically extracts scalability characteristics of a class of deterministic parallel programs. We show with the help of a number of results on the Intel iPSC/860, that predictions are within reasonable bounds.

Sarukkai, Sekhar R.↗

NASA NTRS2001

A Scalable Analysis Toolkit

The Scalable Analysis Toolkit (SAT) project aimed to demonstrate that it is feasible and useful to statically detect software bugs in very large systems. The technical focus of the project was on a relatively new class of constraint-based techniques for analysis software, where the desired facts about programs (e.g., the presence of a particular bug) are phrased as constraint problems to be solved. At the beginning of this project, the most successful forms of formal software analysis were limited forms of automatic theorem proving (as exemplified by the analyses used in language type systems and optimizing compilers), semi-automatic theorem proving for full verification, and model checking. With a few notable exceptions these approaches had not been demonstrated to scale to software systems of even 50,000 lines of code. Realistic approaches to large-scale software analysis cannot hope to make every conceivable formal method scale. Thus, the SAT approach is to mix different methods in one application by using coarse and fast but still adequate methods at the largest scales, and reserving the use of more precise but also more expensive methods at smaller scales for critical aspects (that is, aspects critical to the analysis problem under consideration) of a software system. The principled method proposed for combining a heterogeneous collection of formal systems with different scalability characteristics is mixed constraints. This idea had been used previously in small-scale applications with encouraging results: using mostly coarse methods and narrowly targeted precise methods, useful information (meaning the discovery of bugs in real programs) was obtained with excellent scalability.

Aiken, Alexander↗

NASA NTRS2002

The Efficiency and the Scalability of an Explicit Operator on an IBM POWER4 System

We present an evaluation of the efficiency and the scalability of an explicit CFD operator on an IBM POWER4 system. The POWER4 architecture exhibits a common trend in HPC architectures: boosting CPU processing power by increasing the number of functional units, while hiding the latency of memory access by increasing the depth of the memory hierarchy. The overall machine performance depends on the ability of the caches-buses-fabric-memory to feed the functional units with the data to be processed. In this study we evaluate the efficiency and scalability of one explicit CFD operator on an IBM POWER4. This operator performs computations at the points of a Cartesian grid and involves a few dozen floating point numbers and on the order of 100 floating point operations per grid point. The computations in all grid points are independent. Specifically, we estimate the efficiency of the RHS operator (SP of NPB) on a single processor as the observed/peak performance ratio. Then we estimate the scalability of the operator on a single chip (2 CPUs), a single MCM (8 CPUs), 16 CPUs, and the whole machine (32 CPUs). Then we perform the same measurements for a chache-optimized version of the RHS operator. For our measurements we use the HPM (Hardware Performance Monitor) counters available on the POWER4. These counters allow us to analyze the obtained performance results.

Frumkin, Michael↗

NASA NTRS2003

Scalability of a Low-Cost Multi-Teraflop Linux Cluster for High-End Classical Atomistic and Quantum Mechanical Simulations

Scalability of a low-cost, Intel Xeon-based, multi-Teraflop Linux cluster is tested for two high-end scientific applications: Classical atomistic simulation based on the molecular dynamics method and quantum mechanical calculation based on the density functional theory. These scalable parallel applications use space-time multiresolution algorithms and feature computational-space decomposition, wavelet-based adaptive load balancing, and spacefilling-curve-based data compression for scalable I/O. Comparative performance tests are performed on a 1,024-processor Linux cluster and a conventional higher-end parallel supercomputer, 1,184-processor IBM SP4. The results show that the performance of the Linux cluster is comparable to that of the SP4. We also study various effects, such as the sharing of memory and L2 cache among processors, on the performance.

Kikuchi, Hideaki↗

NASA NTRS2004

Scalability, Timing, and System Design Issues for Intrinsic Evolvable Hardware

In this paper we address several issues pertinent to intrinsic evolvable hardware (EHW). The first issue is scalability; namely, how the design space scales as the programming string for the programmable device gets longer. We develop a model for population size and the number of generations as a function of the programming string length, L, and show that the number of circuit evaluations is an O(L2) process. We compare our model to several successful intrinsic EHW experiments and discuss the many implications of our model. The second issue that we address is the timing of intrinsic EHW experiments. We show that the processing time is a small part of the overall time to derive or evolve a circuit and that major improvements in processor speed alone will have only a minimal impact on improving the scalability of intrinsic EHW. The third issue we consider is the system-level design of intrinsic EHW experiments. We review what other researchers have done to break the scalability barrier and contend that the type of reconfigurable platform and the evolutionary algorithm are tied together and impose limits on each other.

Hereford, James↗

NASA NTRS2004

Scalable High Performance Computing: Direct and Large-Eddy Turbulent Flow Simulations Using Massively Parallel Computers

This final report contains reports of research related to the tasks "Scalable High Performance Computing: Direct and Lark-Eddy Turbulent FLow Simulations Using Massively Parallel Computers" and "Devleop High-Performance Time-Domain Computational Electromagnetics Capability for RCS Prediction, Wave Propagation in Dispersive Media, and Dual-Use Applications. The discussion of Scalable High Performance Computing reports on three objectives: validate, access scalability, and apply two parallel flow solvers for three-dimensional Navier-Stokes flows; develop and validate a high-order parallel solver for Direct Numerical Simulations (DNS) and Large Eddy Simulation (LES) problems; and Investigate and develop a high-order Reynolds averaged Navier-Stokes turbulence model. The discussion of High-Performance Time-Domain Computational Electromagnetics reports on five objectives: enhancement of an electromagnetics code (CHARGE) to be able to effectively model antenna problems; utilize lessons learned in high-order/spectral solution of swirling 3D jets to apply to solving electromagnetics project; transition a high-order fluids code, FDL3DI, to be able to solve Maxwell's Equations using compact-differencing; develop and demonstrate improved radiation absorbing boundary conditions for high-order CEM; and extend high-order CEM solver to address variable material properties. The report also contains a review of work done by the systems engineer.

Morgan, Philip E.↗

NASA NTRS2005

Vacuum Deployment and Testing of a 4-Quadrant Scalable Inflatable Solar Sail System

Solar sails reflect photons streaming from the sun and transfer momentum to the sail. The thrust, though small, is continuous and acts for the life of the mission without the need for propellant. Recent advances in materials and ultra-low mass gossamer structures have enabled a host of useful missions utilizing solar sail propulsion. The team of L'Garde, Jet Propulsion Laboratories, Ball Aerospace, and Langley Research Center, under the direction of the NASA In-Space Propulsion office, has been developing a scalable solar sail configuration to address NASA s future space propulsion needs. The baseline design currently in development and testing was optimized around the 1 AU solar sentinel mission. Featuring inflatably deployed sub-T(sub g), rigidized beam components, the 10,000 sq m sail and support structure weighs only 47.5 kg, including margin, yielding an areal density of 4.8 g/sq m. Striped sail architecture, net/membrane sail design, and L'Garde's conical boom deployment technique allows scalability without high mass penalties. This same structural concept can be scaled to meet and exceed the requirements of a number of other useful NASA missions. This paper discusses the interim accomplishments of phase 3 of a 3-phase NASA program to advance the technology readiness level (TRL) of the solar sail system from 3 toward a technology readiness level of 6 in 2005. Under earlier phases of the program many test articles have been fabricated and tested successfully. Most notably an unprecedented 4-quadrant 10 m solar sail ground test article was fabricated, subjected to launch environment tests, and was successfully deployed under simulated space conditions at NASA Plum Brook s 30m vacuum facility. Phase 2 of the program has seen much development and testing of this design validating assumptions, mass estimates, and predicted mission scalability. Under Phase 3 a much larger 20 m square test article including subscale vane has been fabricated and tested. A 20 m system ambient deployment has been successfully conducted after enduring Delta-2 launch environment testing. The program will culminate in a vacuum deployment of a 20 m subscale test article at the NASA Glenn s Plum Brook 30 m vacuum test facility to bring the TRL level as close to 6 as possible in 1 g. This focused program will pave the way for a flight experiment of this highly efficient space propulsion technology.

Lichodziejewski, David↗

NASA NTRS2016

Scalable Implementation of Finite Elements by NASA _ Implicit (ScIFEi)

Scalable Implementation of Finite Elements by NASA (ScIFEN) is a parallel finite element analysis code written in C++. ScIFEN is designed to provide scalable solutions to computational mechanics problems. It supports a variety of finite element types, nonlinear material models, and boundary conditions. This report provides an overview of ScIFEi (\Sci-Fi"), the implicit solid mechanics driver within ScIFEN. A description of ScIFEi's capabilities is provided, including an overview of the tools and features that accompany the software as well as a description of the input and output le formats. Results from several problems are included, demonstrating the efficiency and scalability of ScIFEi by comparing to finite element analysis using a commercial code.

Warner, James E.↗

DOE OSTI2025

A scalable and autoclavable oxygen nanosensor platform for metabolic monitoring of Saccharomyces cerevisiae in a bioreactor and other in situ systems

Polymer-encapsulated dye nanoparticle sensors are a valuable approach to achieving in situ analyte measurements with luminescence; however, typical emulsion-based nanosensors are poorly suited for large-scale biological samples due to limitations of synthesis scalability and stability. Branched polyethylenimine (PEI) is a versatile polymer scaffold ideal for constructing nanoparticles with various covalently conjugated moieties due to their high density of reactive primary amines, high water solubility, and biological stability. In this work, we used branched polyethylenimine as a scaffold-based approach for making a stable and scalable ratiometric oxygen sensor. Pt (II) tetracarboxyporphine was used as an oxygen-sensing dye and coumarin 343 as a reference dye, all covalently linked to the PEI scaffold producing a product that could withstand sterilization procedures and easily be scaled. To minimize toxicity from the PEI scaffold, we conjugated it with 2000 MW PEG. The applicability of the sensors was demonstrated in a 200 mL Saccharomyces cerevisiae yeast culture, using orthogonal luminescent and electrochemical oxygen measurements to validate sensor response and measure the metabolic activity of the yeast in our culture. Further, this approach was able to match the sensitivity of our electrochemical measurements while improving upon drawbacks of other luminescent methods of oxygen detection, demonstrating effective monitoring for at least 20 h. Our scaffold-based approach is a modular and easily translatable technology that could be useful in various biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Rapid scalable plasma processing of thin-film Li–La–Zr–O solid-state electrolytes

Solid-state electrolytes, such as lithium lanthanum zirconium oxide (LLZO), show promise as technologies for next-generation high-energy-density batteries, but commercial development has been hindered by a lack of scalable processing methods. Current fabrication methods are costly or require long annealing steps to create dense films. We report an atmospheric pressure blown-arc nitrogen plasma jet process to rapidly form sub-micrometer-thick, dense amorphous LLZO (a-LLZO) films from sol-gel precursors. Films are processed in less than 2 min, an order of magnitude faster than what has previously been reported. We demonstrate 500-nm-thick a-LLZO films processed at 350°C with an ionic conductivity of 2 × 10 −6 S/cm at 30°C and 2 × 10 −3 S/cm at 100°C and a conductance of 19 S at 100°C, the highest conductance of any LLZO phase to date. Here, the films exhibit outstanding smooth surface morphology with low defectivity, advancing atmospheric plasma processing as a scalable processing method for solid-state electrolytes.

25 ENERGY STORAGE↗

DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Net-Zero Ethylene: On the Sustainability, Economics, and Scalability of Synthetic and Fossil Production Pathways

The ethylene industry has contributed over 260 million tons of CO 2 annually, warranting a more sustainable approach. The conversion of CO 2 and H 2 O into ethylene is an appealing technology capable of decoupling chemical production from fossil fuels. However, the large energy demand from this process can potentially lead to adverse environmental impacts. Here, in this article, we critically analyze the economic viability, environmental impact, and scalability of the conversion of CO 2 to ethylene via electrochemical reduction (CO 2 R) and compare this with those of CO 2 -neutral fossil routes utilizing carbon capture and direct air capture. Ethylene derived from CO 2 may be economically competitive under optimistic conditions; however, its large energy requirements pose environmental and scalability challenges. Meeting forecast 2050 ethylene demand using CO 2 R would require half of all electricity produced globally today, and, if powered by solar PV, may have greater CO 2 emissions than current petrochemical ethylene production, negating the purpose of this technology. Using Carbon Capture and Storage and Direct Air Capture to decarbonize petrochemical pathways would require roughly an order of magnitude less energy but would have disproportionate health and climate impacts. Lastly, the analysis highlights the importance of low-carbon energy sources to ensure sustainable CO 2 R ethylene production.

CO2R↗

DOE OSTI2025

Scalable and Regenerable Fibrous Amine-functionalized Matrix (FAM) sorbent for Efficient Enrichment of Critical Minerals from Coal Wastewaters

The poster presents the latest progress on utilizing a commercially scalable flat sheet sorbent for the effective enrichment of critical minerals from coal wastewater. It highlights the performance, scalability, and potential for industrial applications, addressing key challenges in critical recovery from complex wastewater streams.

critical metals↗