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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Simplifying operations with an uplink/downlink integration toolkit

The Operations Engineering Lab (OEL) at JPL has developed a simple, generic toolkit to integrate the uplink/downlink processes, (often called closing the loop), in JPL's Multimission Ground Data System. This toolkit provides capabilities for integrating telemetry verification points with predicted spacecraft commands and ground events in the Mission Sequence Of Events (SOE) document. In the JPL ground data system, the uplink processing functions and the downlink processing functions are separate subsystems that are not well integrated because of the nature of planetary missions with large one-way light times for spacecraft-to-ground communication. Our new closed-loop monitoring tool allows an analyst or mission controller to view and save uplink commands and ground events with their corresponding downlinked telemetry values regardless of the delay in downlink telemetry and without requiring real-time intervention by the user. An SOE document is a time-ordered list of all the planned ground and spacecraft events, including all commands, sequence loads, ground events, significant mission activities, spacecraft status, and resource allocations. The SOE document is generated by expansion and integration of spacecraft sequence files, ground station allocations, navigation files, and other ground event files. This SOE generation process has been automated within the OEL and includes a graphical, object-oriented SOE editor and real-time viewing tool running under X/Motif. The SOE toolkit was used as the framework for the integrated implementation. The SOE is used by flight engineers to coordinate their operations tasks, serving as a predict data set in ground operations and mission control. The closed-loop SOE toolkit allows simple, automated integration of predicted uplink events with correlated telemetry points in a single SOE document for on-screen viewing and archiving. It automatically interfaces with existing real-time or non real-time sources of information, to display actual values from the telemetry data stream. This toolkit was designed to greatly simplify the user's ability to access and view telemetry data, and also provide a means to view this data in the context of the commands and ground events that are used to interpret it. A closed-loop system can prove especially useful in small missions with limited resources requiring automated monitoring tools. This paper will discuss the toolkit implementation, including design trade-offs and future plans for enhancing the automated capabilities.

Murphy, Susan C.↗
NASA NTRS2009

A New View of Radiation-Induced Cancer: Integrating Short- and Long-Term Processes. Part II: Second Cancer Risk Estimation

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

Shuryak, Igor↗
NASA NTRS2015

Thermal Radiometer Signal Processing Using Radiation Hard CMOS Application Specific Integrated Circuits for Use in Harsh Planetary Environments

Thermal radiometers such as proposed for the Europa Clipper flyby mission require low noise signal processing for thermal imaging with immunity to Total Ionizing Dose (TID) and Single Event Latchup (SEL). Described is a second generation Multi- Channel Digitizer (MCD2G) Application Specific Integrated Circuit (ASIC) that accurately digitizes up to 40 thermopile pixels with greater than 50 Mrad (Si) immunity TID and 174 MeV-sq cm/mg SEL. The MCD2G ASIC uses Radiation Hardened By Design (RHBD) techniques with a 180 nm CMOS process node.

Focal Plane Assembly↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
DOE OSTI2022

Local Thermomechanical Processing for Improving Formability of High Strength Aluminum Sheets

Limited room temperature formability hinders the wide-spread use of high strength aluminum alloys in structural body-in-white parts. Stamping or extrusion at warm temperatures or from softer tempers are the current solutions. In this work, our approach is to start with age-hardened sheets from 7xxx and 6xxx family of alloys and improve their formability using local thermomechanical processing only in the regions demanding highest ductility in the forming processes. We achieved local formability improvements with friction stir processing and introduce another process named roller-bending as a concept and showed its feasibility through finite element simulations. Initial results from FSP indicated significant deformation in the processed zones with minimal sheet distortion. FSP also resulted in dynamically recrystallized, fine grained (d < 5 µm) microstructures in the processed regions with textures significantly different from the base material. This resulted in formability improvements of > 30% in 7085-T76 and > 50% in 6111-T6 alloys as measured by minimum bend radius (r/t) ratios established with V-bending tests performed at 90° and 180° bend angles. Based on the encouraging initial results, we envision applicability of these processes in both pre- and post-stamping stages through integration of the process tools as end-effectors to robotic arms.

Nasim, Wahaz↗
NASA NTRS1994

VLSI technology for smaller, cheaper, faster return link systems

Very Large Scale Integration (VLSI) Application-specific Integrated Circuit (ASIC) technology has enabled substantially smaller, cheaper, and more capable telemetry data systems. However, the rapid growth in available ASIC fabrication densities has far outpaced the application of this technology to telemetry systems. Available densities have grown by well over an order magnitude since NASA's Goddard Space Flight Center (GSFC) first began developing ASIC's for ground telemetry systems in 1985. To take advantage of these higher integration levels, a new generation of ASIC's for return link telemetry processing is under development. These new submicron devices are designed to further reduce the cost and size of NASA return link processing systems while improving performance. This paper describes these highly integrated processing components.

Nanzetta, Kathy↗
NASA NTRS2002

Bi-Level Integrated System Synthesis (BLISS) for Concurrent and Distributed Processing

The paper introduces a new version of the Bi-Level Integrated System Synthesis (BLISS) methods intended for optimization of engineering systems conducted by distributed specialty groups working concurrently and using a multiprocessor computing environment. The method decomposes the overall optimization task into subtasks associated with disciplines or subsystems where the local design variables are numerous and a single, system-level optimization whose design variables are relatively few. The subtasks are fully autonomous as to their inner operations and decision making. Their purpose is to eliminate the local design variables and generate a wide spectrum of feasible designs whose behavior is represented by Response Surfaces to be accessed by a system-level optimization. It is shown that, if the problem is convex, the solution of the decomposed problem is the same as that obtained without decomposition. A simplified example of an aircraft design shows the method working as intended. The paper includes a discussion of the method merits and demerits and recommendations for further research.

Sobieszczanski-Sobieski, Jaroslaw↗
DOE OSTI2023

Scalable aqueous-phase fabrication of reduced graphene oxide nanofiltration membranes by an integrated roll-to-roll (R2R) process

Economic fractionation of multicomponent biomass-derived streams is a key challenge in biobased fuels and chemicals production. Kraft black liquor (BL) is generated at ~1 billion tons/yr globally from biomass pulping and contains ~15wt% total solids including lignin, hemicellulose fragments, and inorganics. Membrane-based BL concentration is attractive but challenged by low solute rejections and poor stability in BL, which combines alkaline pH (~13), high dissolved solids content (15+ wt%) and high temperature (70–85°C). Here we discuss the scaled fabrication and characterization of reduced graphene oxide (rGO) nanofiltration membranes by slot die coating on a roll-to-roll (R2R) with integrated vacuum filtration. Here, we obtain high-quality 90×30 cm rGO membranes (referred to as “R2R-rGO membranes” in this work) with ~100 nm average thickness supported on porous poly(ethersulfone) (PES) sheets, and an effective area of 2700cm 2 . We present characterizations of their microstructure and uniformity as mapped over large areas by scanning electron microscopy (SEM), ellipsometry, adhesion test and X-ray photoelectron spectroscopy (XPS). The constructed ellipsometry model for the rGO membrane/PES substrate composite was successfully applied to 48 different locations of the R2R-rGO membranes. The R2R-rGO membranes showed >98% lignin rejection with a steady state flux of ~12 LMH at 50bar in a 15.7wt% total solids (TS) kraft BL stream at 72°C and 2–3 gal/min crossflow rates. Slot die coating on a R2R platform with integrated vacuum filtration can enable rapid fabrication of high-quality GO membranes at scale without organic solvents or volatile organic compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimization on Manifolds via Graph Gaussian Processes

This paper integrates manifold learning techniques within a Gaussian process upper confidence bound algorithm to optimize an objective function on a manifold. Our approach is motivated by applications where a full representation of the manifold is not available and querying the objective is expensive. We rely on a point cloud of manifold samples to define a graph Gaussian process surrogate model for the objective. Query points are sequentially chosen using the posterior distribution of the surrogate model given all previous queries. We establish regret bounds in terms of the number of queries and the size of the point cloud. Several numerical examples complement the theory and illustrate the performance of our method.

Bayesian optimization↗
DOE OSTI2020

Conceptual Basis and Techno-Economic Modeling for Integrated Algal Biorefinery Conversion of Microalgae to Fuels and Products (2019 NREL TEA Update: Highlighting Paths to Future Cost Goals via a New Pathway for Combined Algal Processing)

The report documents the conceptual basis for a new potential Combined Algal Processing design strategy which may allow more flexibility in accommodating different algal biomass feedstock compositions, by enabling upgrading of both protein and carbohydrates in a single step, without a strict requirement for either component to be in soluble or monomeric form, while maintaining effective wet lipid extraction techniques to enable high lipid recoveries. In light of previously-established constraints around algal biomass costs (which are significantly higher than lignocellulosic terrestrial biomass), the present CAP processing strategy reflects an integrated biorefinery concept producing both fuels and value-added chemical coproducts as a means to improve profitability and generate coproduct revenues to help drive down the minimum fuel selling price (MFSP) towards economically viable levels. Namely, this report highlights an integrated CAP biorefinery process and associated technical targets that would be required to achieve U.S. Department of Energy target MFSP goals of $2.5/gallon gasoline equivalent by 2030. This is accomplished by a process involving low-cost seasonal storage of algal biomass during high-growth seasons, rapid flash hydrolysis pretreatment of the biomass, solvent extraction of pretreated biomass, cleanup and fractionation of lipids into triglyceride and free fatty acid fractions, and a series of thermochemical conversion steps to upgrade carbohydrates and protein to hydrocarbon fuels. These steps include mild oxidative treatment (MOT), a process originally investigated at NREL for upgrading lignin, followed by catalytic ketonization and hydrotreating of MOT products to fuels. Isolated triglycerides are sent to a coproduct train, with the base case focused on upgrading to polyurethane foams as a high-value, high-market-volume coproduct.

09 BIOMASS FUELS↗
DOE OSTI2025

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures. In this work, we go beyond single input modalities and explore multimodal large language models (MLLMs) for the analysis of diverse data inputs for automated electrosynthesis reaction mining. We compiled a test dataset of 65 articles (MERMES-T24 set) and employed it to benchmark five prominent MLLMs against two critical tasks: (i) reaction diagram parsing and (ii) resolving cross-modality data interdependencies. The frontrunner MLLM achieved ≥96% accuracy in both tasks, with the strategic integration of single-shot visual prompts and image pre-processing techniques. We integrate this capability into a toolkit named MERMES (multimodal reaction mining pipeline for electrosynthesis). Our toolkit functions as an end-to-end MLLM-powered pipeline that integrates article retrieval, information extraction and multimodal analysis for streamlining and automating knowledge extraction. This work lays the groundwork for the increased utilization of MLLMs to accelerate the digitization of chemistry knowledge for data-driven research.

Leong, Shi Xuan↗
NASA NTRS1995

Integrated planning and scheduling for Earth science data processing

Several current NASA programs such as the EOSDIS Core System (ECS) have data processing and data management requirements that call for an integrated planning and scheduling capability. In this paper, we describe the experience of applying advanced scheduling technology operationally, in terms of what was accomplished, lessons learned, and what remains to be done in order to achieve similar successes in ECS and other programs. We discuss the importance and benefits of advanced scheduling tools, and our progress toward realizing them, through examples and illustrations based on ECS requirements. The first part of the paper focuses on the Data Archive and Distribution (DADS) V0 Scheduler. We then discuss system integration issues ranging from communication with the scheduler to the monitoring of system events and re-scheduling in response to them. The challenge of adapting the scheduler to domain-specific features and scheduling policies is also considered. Extrapolation to the ECS domain raises issues of integrating scheduling with a product-generation planner (such as PlaSTiC), and implementing conditional planning in an operational system. We conclude by briefly noting ongoing technology development and deployment projects being undertaken by HTC and the ISTB.

Boddy, Mark↗
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

Optimization of edge bead removal (EBR) process to enhance defect reduction in optical lithography

Defect reduction remains a critical objective in the integrated circuit manufacturing process, particularly within the highly re-entrant lithography modules where minimizing defects is crucial. Defects at the wafer edge can contaminate lithography modules and downstream processing equipment, leading to redistribution onto the wafer surface and adversely affecting overall device yield. A persistent challenge in the resist coating process is the formation of resist edge beads, driven by the strong Van der Waals attraction of excess photoresist (PR) to itself and the underlying substrate. The edge bead removal (EBR) process is a standard cleaning step designed to eliminate these edge beads and prevent potential contamination. Here, in this study, we identify the sources of EBR induced defects and additional EBR process encroachment toward edge patterning during the EBR cleaning process. This study provides a comprehensive study aimed at optimizing the EBR cleaning process to effectively eliminate EBR-induced defects, thereby enhancing overall device yield. Specifically, we identify three primary defects induced by the EBR cleaning process: rainbow-type, finger-shaped, and teardrop-type defects. Our experimental study reveals that in addition to EBR rinse time, PR cast time is crucial parameters contributing to the formation of these defects. By properly optimizing the PR cast time and EBR rinse time, we were able to remove nearly 100 % of dense clusters of defects that were easily visible even at low magnification optical microscopy throughout the wafer edge. We observed that shorter PR casting times shows edge defects caused by inefficient EBR process because of insufficient time for PR to fully settle causing superfluous PR to continue flowing toward wafer edge during EBR clearing step, leading to partial removal of PR at the wafer edge and the formation of rainbow defects. Proper optimization of both PR casting time and EBR chemistries dispense time is essential to resolve these defects, ensuring efficient EBR cleaning process and improved overall device yield.

42 ENGINEERING↗
NASA NTRS1998

A Web-Based Monitoring System for Multidisciplinary Design Projects

In today's competitive environment, both industry and government agencies are under pressure to reduce the time and cost of multidisciplinary design projects. New tools have been introduced to assist in this process by facilitating the integration of and communication among diverse disciplinary codes. One such tool, a framework for multidisciplinary computational environments, is defined as a hardware and software architecture that enables integration, execution, and communication among diverse disciplinary processes. An examination of current frameworks reveals weaknesses in various areas, such as sequencing, displaying, monitoring, and controlling the design process. The objective of this research is to explore how Web technology, integrated with an existing framework, can improve these areas of weakness. This paper describes a Web-based system that optimizes and controls the execution sequence of design processes; and monitors the project status and results. The three-stage evolution of the system with increasingly complex problems demonstrates the feasibility of this approach.

Rogers, James L.↗
DOE OSTI2018

Metal 3D Printing of Low-NOX Fuel Injectors with Integrated Temperature Sensors (Final Technical Report)

This technical report presents the exploration of design and prototyping of an Oxy-fuel injector with integrated temperature sensing capabilities using Additive Manufacturing (AM) technology. The AM process has proven itself as a viable method to fabricate complex shapes for custom-designed metallic components rapidly. The lack of assembly requirements and the virtually unlimited geometrical complexity renders the AM process particularly attractive for fabricating complex energy system components. The unique layer-by-layer fabrication technique allows the embedding of sensors within complex components early in the design process. Sensors can be embedded (without post-production component modifications) in AM-fabricated components through two distinct processes: Stop and Go or Post-Integration. The Stop and Go fabrication process allows sensor placement within a cavity during fabrication; where the process is allowed to continue upon sensor placement. Post-integration process supports selective build of customized compartments for sensors within the part. The Stop and Go process requires an extremely accurate re-alignment of the powder-bed during the restart process. Additionally, metallization and shorting of sensors due to a considerably high temperature of the AM process creates significant fabrication challenges and limit the types of sensors that can be embedded. The Post-Integration of sensors is a practical alternative for components that can be effectively designed and fabricated with pre-built complex sensor compartments without the need for post-production component modifications. The proposed effort aimed at exploring the fabrication of an oxy-fuel injector designed for high-pressure Oxy-Combustion applications (Combustor for Directly Heated Supercritical Power Cycle) with integrated temperature measurement capabilities using the AM technique. Since the current design methodology of injectors is based on conventional fabrication techniques (e.g., multi-step machining and welding processes), a new paradigm of design methodology needs to be developed for their adaptation in the AM fabrication process. One of the most challenging issues addressed in powder bed fusion is the removal of powder from internal channels/cavities as the powder to be removed has been lightly sintered during the fabrication process. In this research, a major task has been assigned to developing and evaluating powder removal techniques that will ultimately be used when removing sintered powder from cavities/channels used for sensor placement. Achieving thorough powder removal will permit the incorporation of intricate cavities, integrated fasteners, or other novel features to incorporate sensors into parts directly post-fabrication – allowing for the novel, AM-based design practices to be developed and employ for sensor integration. The designed injector was initially tested at atmospheric conditions to review its successful operation. The tests were carried out for different firing inputs; with a minimum of 55 kW and a maximum of 275 kW. Later tests were carried out for pressurized conditions between 82 kW to 275 kW firing input. A pressure of 16.35bar was observed in the combustion chamber pressure during the pressurized test of 275 kW firing input; test duration was 15 seconds. Integrated thermocouples within the injector provided temperature data for test operations. The data revealed during the atmospheric condition the injector temperature is almost unaffected by the combustion. However, during the pressurized condition, the injector temperature rapidly up to 205°C within 15 seconds; at a 275 kW firing input.

42 ENGINEERING↗
NASA NTRS2006

The Glory Program: Global Science from a Unique Spacecraft Integration

The Glory program is an Earth and Solar science mission designed to broaden science community knowledge of the environment. The causes and effects of global warming have become a concern in recent years and Glory aims to contribute to the knowledge base of the science community. Glory is designed for two functions: one is solar viewing to monitor the total solar irradiance and the other is observing the Earth s atmosphere for aerosol composition. The former is done with an active cavity radiometer, while the latter is accomplished with an aerosol polarimeter sensor to discern atmospheric particles. The Glory program is managed by NASA Goddard Space Flight Center (GSFC) with Orbital Sciences in Dulles, VA as the prime contractor for the spacecraft bus, mission operations, and ground system. This paper will describe some of the more unique features of the Glory program including the integration and testing of the satellite and instruments as well as the science data processing. The spacecraft integration and test approach requires extensive analysis and additional planning to ensure existing components are successfully functioning with the new Glory components. The science mission data analysis requires development of mission unique processing systems and algorithms. Science data analysis and distribution will utilize our national assets at the Goddard Institute for Space Studies (GISS) and the University of Colorado's Laboratory for Atmospheric and Space Physics (LASP). The Satellite was originally designed and built for the Vegetation Canopy Lidar (VCL) mission, which was terminated in the middle of integration and testing due to payload development issues. The bus was then placed in secure storage in 2001 and removed from an environmentally controlled container in late 2003 to be refurbished to meet the Glory program requirements. Functional testing of all the components was done as a system at the start of the program, very different from a traditional program. The plan for Glory is to minimize any changes to the spacecraft in order to meet the Glory requirements. This means that the instrument designs must adhere to the existing interfaces and capabilities as much as possible. Given Glory's unique history and the potential science return, the program is one of significant value to both the science community and the world. The findings Glory promises will improve our understanding of the drivers for global climate change for a minimal investment. The program hopes to show that reuse of existing government assets can result in a lower cost, and fully successful mission.

Bajpayee Jaya↗