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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

A Hyperbolic Ontology Visualization Tool for Model Application Programming Interface Documentation

Spacecraft modeling, a critically important portion in validating planned spacecraft activities, is currently carried out using a time consuming method of mission to mission model implementations and integration. A current project in early development, Integrated Spacecraft Analysis (ISCA), aims to remedy this hindrance by providing reusable architectures and reducing time spent integrating models with planning and sequencing tools. The principle objective of this internship was to develop a user interface for an experimental ontology-based structure visualization of navigation and attitude control system modeling software. To satisfy this, a number of tree and graph visualization tools were researched and a Java based hyperbolic graph viewer was selected for experimental adaptation. Early results show promise in the ability to organize and display large amounts of spacecraft model documentation efficiently and effectively through a web browser. This viewer serves as a conceptual implementation for future development but trials with both ISCA developers and end users should be performed to truly evaluate the effectiveness of continued development of such visualizations.

mission operations system (MOS)↗
DOE OSTI2020

A New Approach to Indoor Characterization of PV Module Energy Yield Parameters

Temperature and solar irradiance are among the most relevant parameters that affect the energy yield of photovoltaic cells and modules. A rise in the module temperature leads to a significant decrease in the open circuit voltage and a small increase in the short circuit current. Here we use a new tool to determine temperature coefficients as well as to assess power rating of multi c-Si, mono c-Si, CdTe, and CIGS-based PV modules in controlled indoor conditions per IEC 60891 and IEC 61853-1. We use the tool to explore how nonuniformities in module temperature affect the accuracy of the temperature coefficients.

14 SOLAR ENERGY↗
NASA NTRS2015

TankSIM: A Cryogenic Tank Performance Prediction Program

Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

Bolshinskiy, L. G.↗
NASA NTRS1999

The Identification and Modeling of Visual Cue Usage in Manual Control Task Experiments

Many fields of endeavor require humans to conduct manual control tasks while viewing a perspective scene. Manual control refers to tasks in which continuous, or nearly continuous, control adjustments are required. Examples include flying an aircraft, driving a car, and riding a bicycle. Perspective scenes can arise through natural viewing of the world, simulation of a scene (as in flight simulators), or through imaging devices (such as the cameras on an unmanned aerospace vehicle). Designers frequently have some degree of control over the content and characteristics of a perspective scene; airport designers can choose runway markings, vehicle designers can influence the size and shape of windows, as well as the location of the pilot, and simulator database designers can choose scene complexity and content. Little theoretical framework exists to help designers determine the answers to questions related to perspective scene content. An empirical approach is most commonly used to determine optimum perspective scene configurations. The goal of the research effort described in this dissertation has been to provide a tool for modeling the characteristics of human operators conducting manual control tasks with perspective-scene viewing. This is done for the purpose of providing an algorithmic, as opposed to empirical, method for analyzing the effects of changing perspective scene content for closed-loop manual control tasks.

Sweet, Barbara Townsend↗
DOE OSTI2020

Polaron and Spin Dynamics in Organic–Inorganic Lead Halide Perovskite Nanocrystals

Long-lived carrier population and spin-based behavior in lead halide perovskite nanocrystals (NCs) are very interesting for implementing photovoltaic devices with efficiencies exceeding the Shockley–Queisser limit and quantum information processing, respectively. However, a comprehensive understanding of polaron-mediated charge carrier interactions and an accurate description of the spin-polarized states for spintronics are still lacking. Herein, the carrier and spin interactions are studied under controlled conditions in FAPbI 3 and Cs 0.01 FA 0.99 Pb(Br 0.11 I 0.89 ) 3 NCs through ultrafast transient absorption (TA) spectroscopy. At early timescales, TA spectrum shows an asymmetric derivative feature originating from the hot carrier-induced spectral redshift in FAPbI 3 NCs (55 ± 3 meV) and Cs0.01FA0.99Pb(Br0.11I0.89)3 NCs (54 ± 2 meV) at the bandedges that stabilizes to 9 ± 1 and 11 ± 2 meV, respectively, at 1 ps due to the polaron formation. The kinetic analysis indicates that the polaron populations in FAPbI3 and Cs 0.01 FA 0.99 Pb(Br 0.11 I 0.89 ) 3 NCs decay with an average lifetime of 657 ± 34 and 532 ± 28 ps, respectively. The circular polarization-resolved TA reveals that polaron formation can control spin relaxation in NCs, thus providing a powerful tool to explore the development of their prospective applications in spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Terahertz-polarizing effect based on geometric anisotropy of Ti 3 C 2 T x MXene nanosheets

Two-dimensional (2D) nanomaterials have garnered considerable attention due to their unique properties, such as thinness and excellent electronic properties. The inherent anisotropy of 2D nanomaterials, which is characterized by their high aspect ratio, can maximize the directional functionality to enhance the conductivity and utilization of edges. Here, we demonstrate how to utilize the edges of titanium carbide (Ti 3 C 2 T x ) MXene nanosheet to control the linear polarization in the terahertz (THz) frequency range. By a simple and unique vertical alignment exploiting the high surface charge and excellent colloidal dispersibility of MXene nanosheets, MXene nanosheets are vertically oriented along an applied AC electric field. The well-aligned edges justify the THz polarizing effect, revealing outstanding performances such as the broadband coverage in 0.2–1.5 THz and an exceptional extinction ratio reaching 20 dB. Furthermore, we vary the local orientation of the vertical MXene nanosheets by tailoring the applied electric field, enabling spatially controllable polarization capabilities. Our results can provide a generic tool for the utilization of 2D nanomaterials in diverse potential applications in optics and electronics.

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

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗
DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗
DOE OSTI2024

Directing Nanoparticle Organization in Response to Diverse Chemical Inputs

Signaling cascades are crucial for transducing stimuli in biological systems, enabling multiple stimuli to regulate a downstream target with precisely controlled timing and amplifying signals through a series of intermediary reactions. Developing a robust signaling system with such capabilities would be pivotal for programming complex behaviors in synthetic DNA-based molecular devices. However, although “software” such as nucleic acid circuits could potentially be harnessed to relay signals to DNA-based nanostructure hardware, such explorations have been limited. Here, in this study, we develop a platform for transducing a variety of stimuli via messenger-mediated reactions to regulate the release and reloading of gold nanoparticles (AuNPs) in a 3D DNA framework. In the first step, an in vitro transcription circuit is engineered to sense and amplify chemical stimuli, including arbitrary DNA sequences and proteins, producing RNA. In the second step, the RNA releases the DNA-coated AuNPs from the DNA framework via a strand displacement reaction. AuNP reloading is controlled by a separate step driven by degradation of the RNA. Our platform holds promise for applications requiring dynamic multiagent control over DNA-based devices, offering a versatile tool for advanced molecular device engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Large surface conductance and superconductivity in topological insulator microstructures

Controllable geometric manipulation via micromachining techniques provides a promising tool for enhancing useful topological electrical responses relevant to future applications such as quantum information science [P. J. W. Moll, “Focused ion beam microstructuring of quantum matter,” Annu. Rev. Condens. Matter Phys. 9, 147 (2018); Jang et al., “Observation of half-height magnetization steps in Sr 2 RuO 4 ,” Science 331, 186 (2011); Moll et al., “Transport evidence for Fermi-arc-mediated chirality transfer in the Dirac semimetal Cd 3 As 2 ,” Nature 535, 266 (2016); Moll et al., “Evidence for hydrodynamic electron flow in PdCoO 2 ,” Science 351, 1061 (2016)]. Here, we present microdevices fabricated with a focused ion beam from an indium-doped topological insulator Pb 1–x Sn x Te. Furthermore, with the device thickness on the order of 1 μm and an extremely large bulk resistivity, we achieve an unprecedented enhancement of the surface contribution to about 30% of the total conductance near room temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Laser ablation tomography for visualization of root colonization by edaphic organisms

Soil biota have important effects on crop productivity, but can be difficult to study in situ . Laser ablation tomography (LAT) is a novel method that allows for rapid, three-dimensional quantitative and qualitative analysis of root anatomy, providing new opportunities to investigate interactions between roots and edaphic organisms. LAT was used for analysis of maize roots colonized by arbuscular mycorrhizal fungi, maize roots herbivorized by western corn rootworm, barley roots parasitized by cereal cyst nematode, and common bean roots damaged by Fusarium . UV excitation of root tissues affected by edaphic organisms resulted in differential autofluorescence emission, facilitating the classification of tissues and anatomical features. Samples were spatially resolved in three dimensions, enabling quantification of the volume and distribution of fungal colonization, western corn rootworm damage, nematode feeding sites, tissue compromised by Fusarium , and as well as root anatomical phenotypes. Owing to its capability for high-throughput sample imaging, LAT serves as an excellent tool to conduct large, quantitative screens to characterize genetic control of root anatomy and interactions with edaphic organisms. Additionally, this technology improves interpretation of root–organism interactions in relatively large, opaque root segments, providing opportunities for novel research investigating the effects of root anatomical phenes on associations with edaphic organisms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A Graphical Design Approach for Two-Input Single-Output Systems Exploiting Plant/Controller Alignment: Design and Application

Due to the unique structure of two-input single-output (TISO) feedback systems, several closed-loop properties can be characterized using the concepts of plant and controller “directions” and “alignment.” Poor plant/controller alignment indicates significant limitations in terms of closed-loop performance. In general, it is desirable to design a controller that is well aligned with the plant in order to minimize the size of the closed-loop sensitivity functions and closed-loop interactions. Although the concept of alignment can be a useful analysis tool for a given plant/controller pair, it is not obvious how a controller should be designed to achieve good alignment. We present a new controller design approach, based on the PQ method (Schroeck et al., 2001, “On Compensator Design for Linear Time invariant Dual-Input Single-Output Systems,” IEEE/ASME Trans. Mechatronics, 6(1), pp. 50–57), which explicitly incorporates knowledge of alignment into the design process. Here, this is accomplished by providing graphical information about the alignment angle on the Bode plot of the PQ frequency response. We show the utility of this approach through a design example.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗
DOE OSTI2024

USPAS Digital Low-Level RF firmware and software suite (uspas_llrf) v1.0

The USPAS Digital Low-Level RF firmware and software suite was originally developed for the USPAS 2023 LLRF course, for demonstrating the close loop RF control on the BerkeleyLab Marble FPGA carrier and Zest digitizer platform in controlling the RF field for various accelerators. The suite features Register-transfer level (RTL) designs for the board-support layer, digital signal processing and verification test benches, system-on-chip architecture, and Experimental Physics and Industrial Control System (EPICS) support, utilizing a open-source tool chain.

Du, Qiang↗
DOE OSTI2022

TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks

Background: With cancer as one of the leading causes of death worldwide, accurate primary tumor type prediction is critical in identifying genetic factors that can inhibit or slow tumor progression. There have been efforts to categorize primary tumor types with gene expression data using machine learning, and more recently with deep learning, in the last several years. Methods In this paper, we developed four 1-dimensional (1D) Convolutional Neural Network (CNN) models to classify RNA-seq count data as one of 17 highly represented primary tumor types or 32 primary tumor types regardless of imbalanced representation. Additionally, we adapted the models to take as input either all Ensembl genes (60,483) or protein coding genes only (19,758). Unlike previous work, we avoided selection bias by not filtering genes based on expression values. RNA-seq count data expressed as FPKM-UQ of 9,025 and 10,940 samples from The Cancer Genome Atlas (TCGA) were downloaded from the Genomic Data Commons (GDC) corresponding to 17 and 32 primary tumor types respectively for training and validating the models. Results: All 4 1D-CNN models had an overall accuracy of 94.7% to 97.6% on the test dataset. Further evaluation indicates that the models with protein coding genes only as features performed with better accuracy compared to the models with all Ensembl genes for both 17 and 32 primary tumor types. For all models, the accuracy by primary tumor type was above 80% for most primary tumor types. Conclusions: We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. Further optimization of the models is needed to improve the accuracy of certain primary tumor types.

Jones, Sara↗
DOE OSTI2021

In situ/operando soft x-ray spectroscopy of chemical interfaces in gas and liquid environments

Many energy storage and energy conversion systems are based on the complexity of material architecture, chemistry, and interfacial interactions. To understand and thus ultimately control the energy applications calls for in situ/operando characterization tools. Over the years, in situ/operando soft x-ray spectroscopy has been developed for the studies of gas molecules, molecular liquids, catalytic, and electrochemical reactions. Soft x-ray spectroscopy offers electronic structure characterization of materials in energy conversion, energy storage, and catalysis regarding functionality, complexity of material architecture, and chemical interactions. It has been shown how to use the powerful in situ/operando soft x-ray spectroscopy characterization techniques of interfacial phenomena and how to reveal the mechanism of charge transfer and chemical transformation of solid/gas and solid/liquid interfaces of energy storage and catalytic materials in a realistic environment. It has been demonstrated how to overcome the challenge that soft x-rays cannot easily peek into the high-pressure catalytic or liquid electrochemical reactions. Finally, the unique design of in situ/operando soft x-ray spectroscopy instrumentation and fabrication principle and examples of experiments are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Efficiency-Optimized Dual Fuel Engine with In-Cylinder Gasoline/CNG Blending

The objective of the proposed project is to demonstrate targeted blending of gasoline and natural gas as a means to reduce petroleum consumption of light-duty spark-ignition engine vehicles by at least 50%. This goal will be achieved through petroleum displacement with natural gas (NG) combined with a relative engine efficiency improvement in excess of 10% while meeting retrofitability requirements with an anticipated payback period of less than 36 months. Further through NG direct injection (DI) a 10% improvement in power density over the PFI baseline will be demonstrated. The proposed project employs a sound R&D approach and combines experimental work with state-of-the-art computational modeling to be able to demonstrate the ambitious project goals. The project spans a 30 month period and is divided in 3 phases with the initial phase focused on experimental characterization of the gaseous jet structure of the high-pressure NG DI injector which is used to validate the 3D-CFD simulation tool. The phase also includes an experimental demonstration of the fundamental feasibility of the proposed dual-fuel approach on an automotive single-cylinder research engine. The scope of the second phase includes optimization of the combustion system by means of virtual design combined with 3D-CFD analysis. The resulting optimized combustion system will be built and experimentally evaluated by the end of the 12 month period. The third and final phase expands the scope by integrating the engine results in a vehicle level simulation tool with the objective of developing an optimized engine control strategy that maximizes the efficiency benefits attainable with the limited on-board NG supplies. A detailed cost analysis to verify that the 36 month amortization period requirement is met will conclude the proposed effort.

42 ENGINEERING↗
DOE OSTI2018

High Temperature 300°C Measurement While Drilling System

Many countries around the world, including the USA, have untapped geothermal energy potential. Enhanced Geothermal Systems (EGS) technology is needed to economically utilize this resource. Temperatures in some EGS reservoirs can exceed 300°C. To effectively utilize EGS resources, an array of injection and production wells must be accurately placed in the formation fracture network. Therefore, EGS can greatly benefit from a high temperature directional drilling system. Most commercial services for directional drilling systems are rated for 175°C while geothermal wells require operation at much higher temperatures. Two U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) projects have been initiated to develop a 300°C capable directional drilling system, the first developing a drill bit, directional motor, and drilling fluid (award number DE-EE0002782), and the second adding navigation and telemetry systems. This report is for the second project, “High Temperature 300°C Measurement While Drilling System”, award number DE-EE0005505. The “High Temperature 300°C Measurement While Drilling (MWD)” system complements the already developed drilling system with real time navigation capability. It is comprised of 175°C directional measurement electronics including the required sensors for measuring inclination and azimuth in 3 axes. It is embedded in a cooling and temperature isolation system to protect the electronics and sensors from the higher temperature outside the system, which can reach 300°C. Building the cooling and isolation system from non-magnetic materials and keeping a required distance to any magnetic component, such as alternator parts, ensures a high quality measurement of the earth’s magnetic field. This is required to achieve the specified navigation accuracy. The MWD system has a turbine driven alternator that is capable of delivering the required electrical energy to the electronic system at a 300°C borehole temperature. Measured data will be communicated to the surface by mud-pulse-telemetry. For this purpose the tool has a mud-pulse-valve that is controlled by the measurement electronics to establish a serial data communication via the mud stream. The mud-pulse-valve is also built to operate under 300°C borehole conditions. Three prototypes of the 300°C MWD were built and tested. These systems are available for a joint application with the previously developed 300°C drilling system, in a geothermal well.

15 GEOTHERMAL ENERGY↗