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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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Effect of boundary conditions for tangential displacement on upper critical pressure value of cylindrical shell
Critical load for thin plate weakened by elliptic hole that causes macroscopic equilibrium cracks
Viscosity coefficients of liquids near critical points
Interfiber distance and temperature effect on critical aspect ratio in composites
Critical surface between superconducting and normal state determined for commercial niobium stannide ribbon and Nb-Zr wire
Critical fluid flow rate analysis of two-phase nitrogen at stagnation pressure of 25 psia
We present high-resolution measurements of the isothermal susceptibility of pure 3He near the liquid-gas critical point.
This paper proposes the use of Bi-directional Analysis (BDA), an integrated extension of SFMEA and SFTA, as a core assessment technique by which saftey-critical software can be certified.
Large gravity induced density gradients present in ground-based experiments prevent an unambiguous test of universality and scaling predictions near the liquid-gas critical point.
Proper interpretation of critical velocity ionization experiments depends upon understanding the expected results from in-situ or remote sensors. In particular, the 1991 shuttle based CIV experiment had diagnostics.
Although the existence of the critical ionization velocity (CIV) is known from laboratory experiments, no agreement has been reached as to weather CIV exists in the natural space environment.
Critical Facilities Maintenance Assessment (CFMA) was first implemented by NASA following the March 2000 overtest of the High Energy Solar Spectroscopic Imager (HESSI) spacecraft. A sine burst dynamic test using a 40 year old shaker failed. Mechanical binding/slippage of the slip table imparted 10 times the planned force to the test article. There was major structural damage to HESSI. The mechanical "health" of the shaker had not been assessed and tracked to assure the test equipment was in good working order. Similar incidents have occurred at NASA facilities due to inadequate maintenance (e.g., rainwater from a leaky roof contaminated an assembly facility that housed a spacecraft). The HESSI incident alerted NASA to the urgent need to identify inadequacies in ground facility readiness and maintenance practices. The consequences of failures of ground facilities that service these NASA systems are severe due to the high unit value of NASA products.
We develop a new metric, Relative Critical Value Deviation (RCVD), for classifying and predicting software quality.
A new electrostriction technique was developed to measure the isothermal compressibility along isochores and isotherms near the critical point. Initial measurements that validate this new technique will also be presented.
A description of the experimental approach for performing critical point measurements is discussed and results of ground based measurements in preparation for the flight experiment are presented.
This study investigates critical heat flux (CHF) for subcooled flow boiling of n-Perfluorohexane based on results of pre-launch Earth-gravity Mission Sequence Tests (MSTs) of the Flow Boiling and Condensation Experiment (FBCE), which was launched to the International Space Station (ISS) in August 2021. CHF measurements were made in a rectangular channel having a 2.5 mm by 5 mm cross-section and a 114.6-mm long heated segment. Both single-sided and double-sided heating were tested in vertical upflow in Earth gravity for a variety of inlet conditions. The inlet subcooling was varied in the range of 0.4 – 32.0°C and encompassed both near-saturated and highly subcooled conditions. Experimental trends and high-speed video records were investigated to better understand the mechanism of CHF. Overall trends show CHF increases as flow rate and/or inlet subcooling are increased. Flow features from the events around CHF justify the applicability of the Interfacial Lift-off Model and the determination of limiting criteria for its application. The present experimental data are combined with prior databases for various flow orientations with respect to Earth gravity and microgravity data collected on parabolic flights. Predictions are made using the Interfacial Lift-off Model for this consolidated subcooled-inlet FBCE-CHF database. A heat utility ratio was included in the model to capture the effects of subcooling and corresponding thermodynamic non-equilibrium. An overall mean absolute error of 19.04% indicates good predictive capability of the model for both heating configurations, different gravity environments, and a wide range of inlet subcooling.
How do you know a proof is correct? Traditionally, mathematical proofs are socially verified – at least one human, following a set of implicit rules of natural language and logic, determines if the proof is believable. If the proof becomes overly tedious and/or is essential to some safety- or mission-critical application, it becomes necessary to determine the soundness to a higher standard. 'Formal methods' refer to mathematically rigorous techniques and tools that enable specification, design, and verification of hardware and software systems. The specification used in formal methods are statements in a mathematical logic while the formal verifications are deductions in that logic. Formal methods can be difficult or time/resource intensive, but offer a higher level of assurance than standard verification through testing or handwritten proofs. This talk will introduce formal methods, motivated by applications of interest to NASA, including uncrewed aircraft operations in the national airspace, urban air environments, and wildfire areas. The audience will be given a crash course in mechanically verified proofs in the Prototype Verification System (PVS), an interactive theorem prover.
Machine learning is increasingly being used in safety-critical systems, where the public safety requires a rigorous assurance process. We shall outline how assurance processes work for conventional systems and identify the primary difficulty in applying them to machine learning enabled systems. We will then outline a path forward including identifying where considerable basic research remains