Search NASA⌕ Search

SEARCH · Search NASA

Results for “Test Driven Development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Core Physics and Kinetics Calculations for the Fissioning Plasma Core Reactor

Highly efficient, compact nuclear reactors would provide high specific impulse spacecraft propulsion. This analysis and numerical simulation effort has focused on the technical feasibility issues related to the nuclear design characteristics of a novel reactor design. The Fissioning Plasma Core Reactor (FPCR) is a shockwave-driven gaseous-core nuclear reactor, which uses Magneto Hydrodynamic effects to generate electric power to be used for propulsion. The nuclear design of the system depends on two major calculations: core physics calculations and kinetics calculations. Presently, core physics calculations have concentrated on the use of the MCNP4C code. However, initial results from other codes such as COMBINE/VENTURE and SCALE4a. are also shown. Several significant modifications were made to the ISR-developed QCALC1 kinetics analysis code. These modifications include testing the state of the core materials, an improvement to the calculation of the material properties of the core, the addition of an adiabatic core temperature model and improvement of the first order reactivity correction model. The accuracy of these modifications has been verified, and the accuracy of the point-core kinetics model used by the QCALC1 code has also been validated. Previously calculated kinetics results for the FPCR were described in the ISR report, "QCALC1: A code for FPCR Kinetics Model Feasibility Analysis" dated June 1, 2002.

Butler, C.↗
NASA NTRS2009

NASA 2009 Body of Knowledge (BoK) Through-Slicon Via Technology

Through-silicon via (TSV) is the latest in a progression of technologies for stacking silicon devices in three dimensions (3D). Driven by the need for improved performance, methods to use short vertical interconnects to replace the long interconnects found in 2D structures have been developed. The industry is moving past the feasibility (research and development [R and D]) phase for TSV technology into the commercialization phase where economic realities will determine which technologies are adopted. Low-cost fine via hole formation and highly reliable via filling technologies have been demonstrated; process equipment and materials are available. Even though design, thermal, and test issues remain, much progress has been made.

3D packaging↗
NASA NTRS2012

Multiscale Dynamics of Solar Magnetic Structures

Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.

Magnetic fields↗
DOE OSTI2024

Progressive transfer learning for advancing machine learning-based reduced-order modeling

Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML models and effectively develop a new ML model(s) for unseen tasks by optimizing information gates in hidden layers. The p-ROM framework is designed to work with any type of data-driven ROMs. For demonstration purposes, we evaluate the p-ROM with specific Barlow Twins ROMs (p-BT-ROMs) to highlight how progress learning can apply to multiple topological and physical problems with an emphasis on a small training set regime. The proposed p-BT-ROM framework has been tested using multiple examples, including transport, flow, and solid mechanics, to illustrate the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. In both similar and different topologies, p-BT-ROM achieves improved model accuracy with much less training data. For instance, p-BT-ROM with four-parent (i.e., pre-trained models) outperforms the no-parent counterpart trained on data nine times larger. The p-ROM framework is poised to significantly enhance the capabilities of ML-based ROM approaches for scientific and engineering applications by mitigating data scarcity through progressively transferring knowledge.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Development of an interface for an ultrareliable fault-tolerant control system and an electronic servo-control unit

The NASA Ames Research Center sponsors a research program for the investigation of Intelligent Flight Control Actuation systems. The use of artificial intelligence techniques in conjunction with algorithmic techniques for autonomous, decentralized fault management of flight-control actuation systems is explored under this program. The design, development, and operation of the interface for laboratory investigation of this program is documented. The interface, architecturally based on the Intel 8751 microcontroller, is an interrupt-driven system designed to receive a digital message from an ultrareliable fault-tolerant control system (UFTCS). The interface links the UFTCS to an electronic servo-control unit, which controls a set of hydraulic actuators. It was necessary to build a UFTCS emulator (also based on the Intel 8751) to provide signal sources for testing the equipment.

Shaver, Charles↗
NASA NTRS2005

An Overview of Wind-Driven Rovers for Planetary Exploration

The use of in-situ propulsion is considered enabling technology for long duration planetary surface missions. Most studies have focused on stored energy from chemicals extracted from the soil or the use of soil chemicals to produce photovoltaic arrays. An older form of in-situ propulsion is the use of wind power. Recent studies have shown potential for wind driven craft for exploration of Mars, Titan and Venus. The power of the wind, used for centuries to power wind mills and sailing ships, is now being applied to modern land craft. Efforts are now underway to use the wind to push exploration vehicles on other planets and moons in extended survey missions. Tumbleweed rovers are emerging as a new type of wind-driven science platform concept. Recent investigations by the National Aeronautics and Space Administration (NASA) and Jet Propulsion Laboratory (JPL) indicate that these light-weight, mostly spherical or quasi-spherical devices have potential for long distance surface exploration missions. As a power boat has unique capabilities, but relies on stored energy (fuel) to move the vessel, the Tumbleweed, like the sailing ships of the early explorers on earth, uses an unlimited resource the wind to move around the surface of Mars. This has the potential to reduce the major mass drivers of robotic rovers as well as the power generation and storage systems. Jacques Blamont of JPL and the University of Paris conceived the first documented Mars wind-blown ball in 1977, shortly after the Viking landers discovered that Mars has a thin CO2 atmosphere with relatively strong winds. In 1995, Jack Jones, et al, of JPL conceived of a large wind-blown inflated ball for Mars that could also be driven and steered by means of a motorized mass hanging beneath the rolling axis of the ball. A team at NASA Langley Research Center started a biomimetic Tumbleweed design study in 1998. Wind tunnel and CFD analysis were applied to a variety of concepts to optimize the aerodynamic characteristics of the Tumbleweed Rovers. Bare structures, structures carrying sails and a tumbleweed plant (of the Salsola genus) were tested in Langley's wind tunnels. Thomas Estier of the Swiss Federal Institute of Technology developed a memory metal collapsible structure, the Windball. Numerous other researchers have also suggested spherical rovers.

Hajos, Gregory A.↗
NASA NTRS2019

SERVIR: Leveraging the Expertise of a Space Agency and a Development Agency to Increase Impact of Earth Observation in the Developing World

SERVIR is a joint initiative of the National Aeronautics and Space Administration (NASA) and the U.S. Agency for International Development (USAID), in collaboration with leading technical organizations around the world-- called SERVIR hubs--that serve and empower developing countries to use satellite data addressing critical challenges in food security and agriculture; water and water-related disasters; land cover, land use and ecosystems; and weather and climate. Over the past fourteen years, the program has worked with stakeholders in 50 countries across the world, partnered with 390 institutions, and generated and shared over 70 products from 27 satellites and sensors. In that process, around 7,400 specialists have been trained in the application of Earth observation data and technology. In its lifetime, SERVIR has been agile and innovative in shifting from what was essentially an incubator for testing and deploying Earth observation science and technology to making co-development the hallmark of its work, exemplified by both South-South and North-South scientific collaborations. SERVIR’s approach has embodied the concept that to solve really big problems, big, creative solutions are needed. SERVIR represents the world working together to address environmental challenges using spaced-based and geospatial technologies. Aligning with the very meaning of SERVIR, i.e. “to serve,” the program continues to be demand-driven in developing and deploying services (versus one-off products) which address development challenges using geospatial tools and Earth observation science. In 2016, as part of SERVIR’s evolution, USAID and NASA released the ‘SERVIR Service Planning Toolkit,’ a guidance document which provides a framework for how geospatial services can be used to tackle development challenges in a sustained manner. Since then, the Service Planning Toolkit’s systematic approach has begun to catch on in other Earth observation efforts. To improve access and use, SERVIR launched a Service Catalogue in February 2019, a searchable collection of demand-driven geospatial services that use Earth observations to support decision making. SERVIR implementing hub partners –include SERVIR-West Africa at the Agrometeorology, Hydrology and Meteorology (AGRHYMET) Regional Center, in Niamey, Niger; SERVIR-Eastern & Southern Africa at the Regional Centre for Mapping of Resources for Development in Nairobi, Kenya; SERVIR-Hindu Kush Himalaya at the International Centre for Integrated Mountain Development in Kathmandu, Nepal; SERVIR-Mekong at the Asian Disaster Preparedness Center in Bangkok, Thailand; and SERVIR’ -Amazonia, at the International Center for Tropical Agriculture (CIAT) in Cali, Colombia.

Searby, Nancy D.↗
DOE OSTI2025

Coupled THM modeling of bentonite heating and hydration in tank tests with a new temperature-dependent water retention model

This study presents a coupled thermo-hydro-mechanical (THM) model for simulating the heating and hydration behavior of bentonite, a buffer material in deep geological repositories (DGRs). The model incorporates a new temperature-dependent soil water retention curve which captures the thermal-induced shift in water retention behavior. It also distinguishes between liquid and gas permeability, modeling intrinsic gas permeability as a function of accessible porosity to improve vapor transport and desaturation predictions. The model was validated against two large-scale tank tests, demonstrating good agreement with measured temperature, relative humidity, and water inflow data. It revealed a complex porosity evolution driven by thermal expansion, vapor movement, vapor condensation, and hydration-induced swelling during heating and hydration processes. The simulation results also suggest that the permeability of the hydration layer plays a critical role in controlling water intake. Clogging of this layer can significantly reduce the volume of water inflow during the hydration phase. Furthermore, while the model effectively captures key THM behavior, further development of the mechanical constitutive law is required to account for possible thermo-elasto-plastic volume changes and microstructural effects. Overall, the model provides a robust tool for evaluating the evolution of bentonite-based barrier material in DGRs.

Guo, Guanlong [Lawrence Berkeley National Laborato↗
DOE OSTI2025

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗
NASA NTRS1971

Space shuttle main engine definition (phase B). Volume 5: Valves and interconnects

The steady state thermodynamic cycle balance of the single preburner staged combustion engine, coupled with dynamic transient analyses, dictated in detail the location and requirements for each valve defined in this volume. Valve configuration selections were influenced by overall engine and vehicle system weight and failure mode determinations. Modulating valve actuators are external to the valve and are line replaceable. Development and satisfactory demonstration of a high pressure dynamic shaft seal has made this configuration practical. Pneumatic motor driven actuators that use engine pumped hydrogen gas as the working fluid are used. The helium control system is proposed as a module containing a cluster of solenoid actuated valves. The separable couplings and flanges are designed to assure minimum leakage with minimum coupling weight. The deflection of the seal surface in the flange is defined by finite element analysis that has been confirmed with test data. The seal design proposed has passed preliminary pressure cycling and thermal cycling tests.

Schultz, D. F.↗
NASA NTRS2017

Overview of SLS Aeroacoustic Environment Development

The Space Launch System (SLS) ascent aeroacoustic environments provide the externally driven noise levels predicted for vehicle ascent during transonic and supersonic flight, and serve as an important input for component and secondary structure vibroacoustic design criteria. This aerodynamically induced noise is predominantly generated by unsteady flow within the local boundary layer due to free stream interaction with the outer mold line (OML). Additional sources are shear flow interactions, shocks, protuberance flows, and wake flows. This presentation provides an overview of the aeroacoustics discipline along with the SLS environment development process, including wind tunnel testing and general data reduction methods. The state of the discipline is also presented with a summary of aeroacoustic measurement and computational techniques currently on the horizon.

Steva, Thomas↗
DOE OSTI2025

A comparison of surrogate constitutive models for viscoplastic creep simulation of HT-9 steel

Mechanistic microstructure-informed constitutive models for the mechanical response of polycrystals are a cornerstone of computational materials science. However, as these models become increasingly more complex – often involving coupled differential equations describing the effect of specific deformation modes – their associated computational costs can become prohibitive, particularly in optimization or uncertainty quantification tasks that require numerous model evaluations. To address this challenge, surrogate constitutive models that balance accuracy and computational efficiency are highly desirable. Data-driven surrogate models, that learn the constitutive relation directly from data, have emerged as a promising solution. In this work, we develop two local surrogate models for the viscoplastic response of a steel: a piecewise response surface method and a mixture of experts model. These surrogates are designed to adapt to complex material behavior, which may vary with material parameters or operating conditions. The surrogate constitutive models are applied to creep simulations of HT-9 steel, an alloy of considerable interest to the nuclear energy sector due to its high tolerance to radiation damage, using training data generated from viscoplastic self-consistent (VPSC) simulations. In conclusion, we define a set of test metrics to numerically assess the accuracy of our surrogate models for predicting viscoplastic material behavior, and show that the mixture of experts model outperforms the piecewise response surface method in terms of accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Site-specific photo-crosslinking in a double crossover DNA tile facilitated by squaraine dye aggregates: advancing thermally stable and uniform DNA nanostructures

We investigated the role of dichloro-squaraine (SQ) dye aggregates in facilitating thymine–thymine interstrand photo-crosslinking within double crossover (DX) tiles, to develop thermally stable and structurally uniform two-dimensional (2D) DNA-based nanostructures. By strategically incorporating SQ modified thymine pairs, we enabled site-selective [2 + 2] photocycloaddition under 310 nm UV light. Strong dye–dye interactions, particularly through the formation of aggregates, facilitated covalent bond formation between proximal thymines. To evaluate the impact of dye aggregation on crosslinking efficiency, ten DX tile variants with varying SQ-modified thymine positions were tested. Our results demonstrated that SQ dye aggregates significantly enhanced crosslinking, driven by precise SQ-modified thymine dimer placement within the DNA tiles. Analytical techniques, including denaturing PAGE and UV-visible spectroscopy, validated successful crosslinking in DNA tiles with multiple SQ-modified thymine pairs. This non-phototoxic method offers a potential route for creating thermally stable, homogeneous higher-order DNA–dye assemblies with potential applications in photoactive and exciton-based fields such as optoelectronics, nanoscale computing, and quantum computing. Furthermore, the insights from this study establish a foundation for further exploration of advanced DNA–dye systems, enabling the design of next-generation DNA nanostructures with enhanced functional properties.

2D DNA template↗
DOE OSTI2024

Strangers in a foreign land: ‘Yeastizing’ plant enzymes

Abstract Expressing plant metabolic pathways in microbial platforms is an efficient, cost‐effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour‐intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost‐effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data‐driven machine learning framework designed to extract ‘yeastizing’ rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design‐build‐test cycle.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1981

Acoustic ground impedance meter

A compact, portable instrument was developed to measure the acoustic impedance of the ground, or other surfaces, by direct pressure-volume velocity measurement. A Helmholz resonator, constructed of heavy-walled stainless steel but open at the bottom, is positioned over the surface having the unknown impedance. The sound source, a cam-driven piston of known stroke and thus known volume velocity, is located in the neck of the resonator. The cam speed is a variable up to a maximum 3600 rpm. The sound pressure at the test surface is measured by means of a microphone flush-mounted in the wall of the chamber. An optical monitor of the piston displacement permits measurement of the phase angle between the volume velocity and the sound pressure, from which the real and imaginary parts of the impedance can be evaluated. Measurements using a 5-lobed cam can be made up to 300 Hz. Detailed design criteria and results on a soil sample are presented.

Zuckerwar, A. J.↗
NASA NTRS1983

Acoustic ground impedance meter

A compact, portable instrument was developed to measure the acoustic impedance of the ground, or other surfaces, by direct pressure-volume velocity measurement. A Helmholtz resonator, constructed of heavy-walled stainless steel but open at the bottom, is positioned over the surface having the unknown impedance. The sound source, a cam-driven piston of known stroke and thus known volume velocity, is located in the neck of the resonator. The cam speed is a variable up to a maximum 3600 rpm. The sound pressure at the test surface is measured by means of a microphone flush-mounted in the wall of the chamber. An optical monitor of the piston displacement permits measurement of the phase angle between the volume velocity and the sound pressure, from which the real and imaginary parts of the impedance can be evaluated. Measurements using a 5-lobed cam can be made up to 300 Hz. Detailed design criteria and results on a soil sample are presented. Previously announced in STAR as N82-17476

Zuckerwar, A. J.↗
NASA NTRS2015

Non-Contact Thermal Characterization of NASA's HERMeS Hall Thruster

The thermal characterization test of NASA's 12.5-kW Hall Effect Rocket with Magnetic Shielding has been completed. This thruster was developed to support a number of potential Solar Electric Propulsion Technology Demonstration Mission concepts, including the Asteroid Redirect Robotic Mission concept. As a part of the preparation for this characterization test, an infrared-based, non-contact thermal imaging system was developed to measure the temperature of various thruster surfaces that are exposed to high voltage or plasma. An in-situ calibration array was incorporated into the setup to improve the accuracy of the temperature measurement. The key design parameters for the calibration array were determined in a separate pilot test. The raw data from the characterization test was analyzed though further work is needed to obtain accurate anode temperatures. Examination of the front pole and discharge channel temperatures showed that the thruster temperature was driven more by discharge voltage than by discharge power. Operation at lower discharge voltages also yielded more uniform temperature distributions than at higher discharge voltages. When operating at high discharge voltage, increasing the magnetic field strength appeared to have made the thermal loading azimuthally more uniform.

Hall Thrusters↗
NASA NTRSDate not supplied

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗