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At least 127 records · Page 7

Electric field effects on a near-critical fluid in microgravity

The effects of an electric field on a sample of SF6 fluid in the vicinity of the liquid-vapor critical point is studied. The isothermal increase of the density of a near-critical sample as a function of the applied electric field was measured. In agreement with theory, this electrostriction effect diverges near the critical point as the isothermal compressibility diverges. Also as expected, turning on the electric field in the presence of density gradients can induce flow within the fluid, in a way analogous to turning on gravity. These effects were observed in a microgravity environment by using the Critical Point Facility which flew onboard the Space Shuttle Columbia in July 1994 as part of the Second International Microgravity Laboratory Mission. Both visual and interferometric images of two separate sample cells were obtained by means of video downlink. The interferometric images provided quantitative information about the density distribution throughout the sample. The electric field was generated by applying 500 Volts to a fine wire passing through the critical fluid.

Zimmerli, G.↗

Critical radiation fluxes and luminosities of black holes and relativistic stars

The critial luminosity at which the outward force of radiation balances the inward force of gravity plays an important role in many astrophysical systems. We present expressions for the radiation force on particles with arbitrary cross sections and analyze the radiation field produced by radiating matter, such as a disk, ring, boundary layer, or stellar surface, that rotates slowly around a slowly rotating gravitating mass. We then use these results to investigate the critical radiation flux and, where possible, the critical luminosity of such a system in genral relativity. We demonstrate that if the radiation source is axisymmetric and emission is back-front symmetric with repect to the local direction of motion of the radiating matter, as seen in the comoving frame, then the radial component of the radiation flux and the diagonal components of the radiation stress-energy tensor outside the source are the same, to first order in the rotation rates, as they would be if the radiation source and gravitating mass were not rotating. We argue that the critical radiation flux for matter at rest in the locally nonrotating frame is often satisfactory as an astrophysical benchmark flux and show that if this benchmark is adopted, many of the complications potentially introduced by rotation of the radiation source and the gravitating mass are avoided. We show that if the radiation field in the absence of rotation would be spherically symmetric and the opacity is independent of frequency and direction, one can define a critical luminosity for the system that is independent of frequency and direction, one can define a critical luminosity for the system that is independent of the spectrum and angular size of the radiation source and is unaffected by rotation of the source and mass and orbital motion of the matter, to first order. Finally, we analyze the conditions under which the maximum possible luminosity of a star or black hole powered by steady spherically symmetric radial accretion is the same in general relativity as in the Newtonian limit.

Lamb, Frederick K.↗

Zeno: Critical Fluid Light Scattering Experiment

The Zeno (Critical Fluid Light Scattering) experiment is the culmination of a long history of critical fluid light scattering in liquid-vapor systems. The major limitation to making accurate measurements closer to the critical point was the density stratification which occurs in these extremely compressible fluids. Zeno was to determine the critical density fluctuation decay rates at a pair of supplementary angles in the temperature range 100 mK to 100 (mu)K from T(sub c) in a sample of xenon accurately loaded to the critical density. This paper gives some highlights from operating the instrument on two flights March, 1994 on STS-62 and February, 1996 on STS-75. More detail of the experiment Science Requirements, the personnel, apparatus, and results are displayed on the Web homepage at http://www.zeno.umd.edu.

Gammon, Robert W.↗

Forced Convection Boiling and Critical Heat Flux of Ethanol in Electrically Heated Tube Tests

Electrically heated tube tests were conducted to characterize the critical heat flux (transition from nucleate to film boiling) of subcritical ethanol flowing at conditions relevant to the design of a regeneratively cooled rocket engine thrust chamber. The coolant was SDA-3C alcohol (95% ethyl alcohol, 5% isopropyl alcohol by weight), and tests were conducted over the following ranges of conditions: pressure from 144 to 703 psia, flow velocities from 9.7 to 77 ft/s, coolant subcooling from 33 to 362 F, and critical heat fluxes up to 8.7 BTU/in(exp 2)/sec. For the data taken near 200 psia, critical heat flux was correlated as a function of the product of velocity and fluid subcooling to within +/- 20%. For data taken at higher pressures, an additional pressure term is needed to correlate the critical heat flux. It was also shown that at the higher test pressures and/or flow rates, exceeding the critical heat flux did not result in wall burnout. This result may significantly increase the engine heat flux design envelope for higher pressure conditions.

Meyer, Michael L.↗

The Human Space Life Sciences Critical Path Roadmap Project: A Strategy for Human Space Flight through Exploration-Class Missions

The product of the critical path roadmap project is an integrated strategy for mitigating the risks associated with human exploration class missions. It is an evolving process that will assure the ability to communicate the integrated critical path roadmap. Unlike previous reports, this one will not sit on a shelf - it has the full support of the JSC Space and Life Sciences Directorate (SA) and is already being used as a decision making tool (e.g., budget and investigation planning for Shuttle and Space Station mission). Utility of this product depends on many efforts, namely: providing the required information (completed risk data sheets, critical question information, technology data). It is essential to communicate the results of the critical path roadmap to the scientific community - this meeting is a good opportunity to do so. The web site envisioned for the critical path roadmap will provide the capability to communicate to a broader community and to track and update the system routinely.

Sawin, Charles F.↗

Shear Thinning Near the Critical Point of Xenon

We measured shear thinning, a viscosity decrease ordinarily associated with complex liquids, near the critical point of xenon. The data span a wide range of reduced shear rate: 10(exp -3) < gamma-dot tau < 700, where gamma-dot tau is the shear rate scaled by the relaxation time tau of critical fluctuations. The measurements had a temperature resolution of 0.01 mK and were conducted in microgravity aboard the Space Shuttle Columbia to avoid the density stratification caused by Earth's gravity. The viscometer measured the drag on a delicate nickel screen as it oscillated in the xenon at amplitudes 3 mu,m < chi (sub 0) >430 mu, and frequencies 1 Hz < omega/2 pi < 5 Hz. To separate shear thinning from other nonlinearities, we computed the ratio of the viscous force on the screen at gamma-dot tau to the force at gamma-dot tau approximates 0: C(sub gamma) is identical with F(chi(sub 0), omega tau, gamma-dot tau )/F)(chi(sub 0, omega tau, 0). At low frequencies, (omega tau)(exp 2) < gamma-dot tau, C(sub gamma) depends only on gamma-dot tau, as predicted by dynamic critical scaling. At high frequencies, (omega tau)(exp 2) > gamma-dot tau, C(sub gamma) depends also on both x(sub 0) and omega. The data were compared with numerical calculations based on the Carreau-Yasuda relation for complex fluids: eta(gamma-dot)/eta(0)=[1+A(sub gamma)|gamma-dot tau|](exp - chi(sub eta)/3+chi(sub eta)), where chi(sub eta) =0.069 is the critical exponent for viscosity and mode-coupling theory predicts A(sub gamma) =0.121. For xenon we find A(sub gamma) =0.137 +/- 0.029, in agreement with the mode coupling value. Remarkably, the xenon data close to the critical temperature T(sub c) were independent of the cooling rate (both above and below T(sub c) and these data were symmetric about T(sub c) to within a temperature scale factor. The scale factors for the magnitude of the oscillator s response differed from those for the oscillator's phase; this suggests that the surface tension of the two-phase domains affected the drag on the screen below T(sub c).

Zimmerli, Gregory A.↗

Determining the Relative Criticality of Diverse Exploration Risks in NASA's Human Research Program

The mission of NASA s Human Research Program (HRP) is to understand and reduce the risk to crew health and performance in exploration missions. The HRP addresses 27 specific risks, primarily in the context of Continuous Risk Management. Each risk is evaluated in terms of two missions (a six month stay on the Moon and a thirty month round trip to Mars) and three types of consequences (in-mission crew health, post-mission crew health, and in-mission performance). The lack of a common metric between the three consequence scales, such as financial costs or quality adjusted life years lost, makes it difficult to compare the relative criticality of the risks. We are, therefore, exploring the use of a ternary scale of criticality based on the common metric of influencing an operational decision. The three levels correspond to the level of concern the risk generates for a "go/no-go" decision to launch a mission: 1) no-go; 2) go with significant reservations; 3) go. The criticality of each of the 27 risks is scored for the three types of consequence in both types of mission. The scores are combined to produce an overall criticality rating for each risk. The overall criticality rating can then be used to guide the prioritization of resources to affect the greatest amount of risk reduction.

Kundrot, Craig E.↗

Critical Questions for Space Human Factors

Traditional human factors contributions to NASA's crewed space programs have been rooted in the classic approaches to quantifying human physical and cognitive capabilities and limitations in the environment of interest, and producing recommendations and standards for the selection or design of mission equipment. Crews then evaluate the interfaces, displays, or equipment, and with the assistance of human factors experts, improvements are made as funds, time, control documentation, and weight allow. We have come a long way from the early spaceflight days, where men with the ' right stuff were the solution to operating whatever equipment was given to them. The large and diverse Shuttle astronaut corps has impacted mission designs to accommodate a wide range of human capabilities and preferences. Yet with existing long duration experience, we have seen the need to address a different set of dynamics when designing for optimal crew performance: critical equipment and mission situations degrade, and human function changes with mission environment, situation, and duration. Strategies for quantifying the critical nature of human factors requirements are being worked by NASA. Any exploration-class mission will place new responsibilities on mission designers to provide the crew with the information and resources to accomplish the mission. The current duties of a Mission Control Center to monitor system status, detect degradation or malfunction, and provide a proven solution, will need to be incorporated into on-board systems to allow the crew autonomous decision-making. The current option to resupply and replace mission systems and resources, including both vehicle equipment and human operators, will be removed, so considerations of maintenance, onboard training, and proficiency assessment are critical to providing a self-sufficient crew. As we 'move in' to the International Space Station, there are tremendous opportunities to investigate our ability to design for autonomous crews. Yet prioritizing the research that can and should be done by NASA will be based on the critical nature of the issues, and the impact of the individual research questions on mission design. The risks to crew health and safety associated with answering critical human factors issues must be properly included and communicated in order to support the Agency's decisions regarding future space programs.

Woolford, Barbara↗

Surface Hold Advisor Using Critical Sections

The Surface Hold Advisor Using Critical Sections is a system and method for providing hold advisories to surface controllers to prevent gridlock and resolve crossing and merging conflicts among vehicles traversing a vertex-edge graph representing a surface traffic network on an airport surface. The Advisor performs pair-wise comparisons of current position and projected path of each vehicle with other surface vehicles to detect conflicts, determine critical sections, and provide hold advisories to traffic controllers recommending vehicles stop at entry points to protected zones around identified critical sections. A critical section defines a segment of the vertex-edge graph where vehicles are in crossing or merging or opposite direction gridlock contention. The Advisor detects critical sections without reference to scheduled, projected or required times along assigned vehicle paths, and generates hold advisories to prevent conflicts without requiring network path direction-of-movement rules and without requiring rerouting, rescheduling or other network optimization solutions.

Law, Caleb Hoi Kei↗

An Astronaut's Risk of Experiencing a Critical Impact from Lunar Ejecta During Lunar EVA

The Moon is under constant bombardment by meteoroids. When the meteoroid is large, the impact craters the surface, launching crater ejecta far from the impact potentially threatening astronauts on the lunar surface. In the early 1960’s, the ejecta impact flux was thought no more than the sporadic meteoroid flux but with speeds one to two orders of magnitude smaller. However, the Lunar Module designers realized by 1965 that meteoroid bumpers do not perform well at the smaller ejecta impact speeds. Their estimates of the Lunar Module risk of penetration by ejecta were 25 to 50% of the total risk. This was in spite of the exposure time to ejecta being only a third of that to sporadic meteoroids. The standard committee based the 1969 NASA SP-8013 lunar ejecta environment on Zook’s 1967 flux analysis and Gault, Shoemaker and Moore’s 1963 test data for impacts into solid basalt targets. However, Zook noted in his 1967 analysis, that if the lunar surface was composed of soil, that the ejected soil particles would be smaller than ejected basalt fragments and that the ejection speeds would be smaller. Both effects contribute to reducing the risk of a critical failure due to lunar ejecta. The authors revised Zook’s analysis to incorporate soil particle size distributions developed from analysis of Apollo lunar soil samples and ejected mass as a function of ejecta speed developed from coupling parameter analyses of soil impact-test data. The authors estimated EVA risk by assuming failure occurs at a critical impact energy. At these impact speeds, this might be true for suit hard and soft goods. However, these speeds are small enough that there may be significant strength effects that require new test data to modify the hypervelocity critical energy failure criterion. With these caveats, Christiansen, Cour-Palais and Freisen list the critical energy of the ISS EMU hard upper torso as 44 J and the helmet and visor as 71 J at hypervelocity. The authors then assumed that the lunar EVA suit fails at 50 J critical energy. This results in a 1,700,000 years mean time to failure using the results of this analysis and a 3,800 years mean time to failure using NASA SP-8013.

Bjorkman, Michael D.↗

Utilization of Airborne Observations to Assess Model Parametrizations of Critical RH Profiles in the Arctic Ocean

Observational paucity is a reality in the Arctic Ocean. This is especially true for near-surface variables such as temperature, moisture, heat fluxes and BL clouds. As a result, modeling has become one of the major avenues for understanding current and future Arctic trends. Reanalyses are frequently used to force global ocean circulation and sea-ice models. But in northern high latitudes, model integrations and reanalyses are known to have large uncertainties in temperature and humidity profiles, and in boundary layer cloudiness. These are common sources of error in the surface radiative budget terms.An important way to diagnose these biases spatially and temporally is by using satellite remote sensing data. However, remotely-sensed observations also have large uncertainties, especially in near-surface temperature and relative humidity profiles.In situ observational studies are important in bridging our knowledge gap in regions such as the Arctic Ocean. Here, we utilize airborne and ship observations from the ARISE, ACME-IV, and ASCOS campaigns to construct critical relative humidity (RH) profiles over the Beaufort Sea. Such profiles are used as parameterization inputs in the NASA GOES global model to derive the total water condensate in a model grid-box, which determines the cloud fraction. Currently, the critical RH profiles are derived by global AIRS data, relaying mostly on mid-latitude regions, which are not necessarily relevant to the Arctic.We derive campaign-wide mean, standard deviation, and critical RH values, for grid size of 50x50 km and altitude bins between 50 to 400 m, covering both open-ocean and sea-ice covered regions. We compare profiles over open ocean and sea-ice, and look at correlations between the observed critical RH values and water condensate (by cloud number concentration) from observations versus the modeled ones. We then input our calculated values of minimal critical RH values into a set of GEOS single column model (SCM) simulations over the ARISE and ASCOS regions and compare the differences between the predicted values of cloud liquid water path (LWP), ice water path (IWP) and surface fluxes with the observed ones under the range of input parameterizations. Finally, we discuss the implications on surface radiative budget predictions in this region.

Segal-Rozenhaimer, Michal↗

The role of AI in detecting and mitigating human errors in safety-critical industries: A review

For safety-critical industries, human error (HE) presents continual risks to system productivity, reliability and safety. Artificial intelligence (AI) and machine learning (ML) methods have emerged as promising approaches to understand, categorize and mitigate the risk of HE in safety-critical industries. Furthermore, this review offers an examination of the current landscape regarding the utilization of AI/ML with regards to HE in safety-critical industries, categorizing literature into descriptive modeling, predictive modeling, prescriptive modeling, and generative modeling techniques. Additionally, the review aims to provide insights regarding themes in literature, challenges, and future research directions. Findings of the review suggest that AI/ML methods can prove useful in addressing the HE problem across safety-critical industries.

42 ENGINEERING↗

NEWTS Economic Data Dashboard: Critical Materials for Energy

The NEWTS Economic Data Dashboard: Critical Materials for Energy is an economic screening tool for assessing the concentration and potential value of the 18 critical materials for energy in fossil energy-related wastewater across the United States. Datasets used to develop the dashboard and complete economic calculations are available as supplementary downloads. These resources were developed primarily using geochemical composition and volume data from the NEWTS Integrated dataset (version 1.0). Energy-related wastewater types presented in the dashboard include produced water (PW), brackish groundwater (BW), acid mine drainage (AMD), coal combustion residual leachate (CCRL), power plant flue gas desulfurization wastewater (FGD), and geothermal fluids. The concentrations of the following critical minerals were included in the analysis, when available: Al, Co, Cu, Dy, F, Ga, Ge, C, Ir, Li, Mg, Mn, Nd, Ni, Pt, Pr, Si, Tb. This economic screening tool was built to support identification of promising critical mineral feedstocks and economic research targets.

Critical Minerals; Critical Minerals and Materials↗

Updating Critical Temperature Calculations for Several Secondary High Explosives

In designing experiments where high explosives (HEs) are heated, it is important to have an understanding of where thermal runaway may occur. This determination is often done by using the Frank-Kamenetskii (FK) equation. For several highly-studied HEs, the parameters necessary for FK calculations are typically referenced from decades-old literature, and more recent experimental data have shown that these values require adjustment. For example, some of the legacy parameters dangerously overpredict the critical temperature by tens of degrees relative to more recent observed values. Herein, we first summarize historical results and highlight the importance of insulation effects when estimating critical temperatures for small samples, which is especially relevant to small-scale aging, compatibility, and characterization experiments. Here, we then present updated FK parameters for several common secondary CHNO HEs like RDX, HMX, PETN, and TATB, as well as the first reported values for 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105). Our updated parameters produce critical-temperature curves that are consistent with both mm-scale differentical scanning calorimetry (DSC) measurements and cm-scale data from the Lawrence Livermore National Laboratory one-dimensional time-to-explosion (ODTX) experiment. In analyzing the critical temperature versus sample size curves derived from the transcendental FK equation, we discovered that these curves are remarkably well described by a simple power-law function with a universal power of 0.142 and a HE-specific scaling factor.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗

Enhancement of the photon emission rate near the QCD critical point

We compute photon emission rate enhancement near the QCD critical point using an effective theory of dynamic critical phenomena and derive a universal photon spectrum. The emission rate scales similar to conductivity, increasing with the correlation length (𝜉), diverging at the critical point. The spectrum exhibits 𝜔⁢𝑑⁢𝑁 𝛾 /𝑑 3 ⁢𝑘 ∝ 𝜔 −1/2 in the scaling regime, with the transition occurring at a frequency comparable to shear damping rate 𝜔 ∼ 𝛾 𝜂 /𝜉 2 , reflecting the nonequilibrium properties of the near-critical liquid.

dynamic critical phenomena↗

Fuel Debris Monitoring Collaboration and Experiences in Criticality Monitoring

Fukushima Daiichi fuel debris removal provides technical challenges and opportunities for the international criticality safety community. The US DOE-NCSP (Nuclear Criticality Safety Program) and France (IRSN) will support 1F fuel debris efforts through collaboration on real-time criticality monitoring. This work will describe a collaboration that is starting soon and will also describe previous efforts associated with criticality experiments and neutron analysis of unknown systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗