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At least 955 records · Page 53

Developmental and Cryogenic Thermal Vacuum (TVAC) Testing Lessons Learned

Developmental thermal vacuum (TVAC) testing is a critical step in maturing hardware designs and validating performance prior to flight qualification. Unlike qualification or acceptance testing, developmental testing provides flexibility to explore design margins, uncover integration challenges, and refine test approaches before formal verification activities begin. This presentation highlights the value of developmental testing while sharing common pitfalls encountered during developmental TVAC campaigns. Lessons learned from hands-on testing experience, including extensive developmental testing at cryogenic temperatures, will be shared in this presentation. Topics include test planning and preparation, instrumentation strategies, contamination control considerations, troubleshooting unexpected anomalies, and approaches for staying on schedule while meeting test objectives. The audience will gain practical insights and best practices that can improve test efficiency, reduce risk, and enhance the overall success of future developmental TVAC efforts.

Mackenzie Byrnes↗

Filament extension atomizers: A study of integration potential into spray dryers for high-viscosity and non-Newtonian fluids

Filament extension atomizers (FEAs) are an emerging class of spray nozzles designed to atomize high-viscosity and non-Newtonian fluids that are challenging for conventional pressure or two-fluid nozzles. In this study, we investigate the influence of roller geometry, surface velocity, roller material, and fluid rheology on the atomization performance of FEA systems using concentrated whey protein suspensions (50–70 wt. %). Extensional and shear rheology experiments, along with high-speed imaging and particle image velocimetry, reveal that filament breakup dynamics are governed by competition between inertial, capillary, and viscoelastic stresses. High roller rotational velocity leads to narrower spray cones, contradicting rheology experiments and suggests a significant inertial contribution to filament breakup. Smaller rollers operating at the same rotational velocity led to broader spray cones consistent with expectations. An FEA nozzle was integrated into a conventional dryer producing particles in the 100 μm range. Results suggest that FEA technology enables atomization of highly viscous fluids at industrially relevant spray cone angles similar to those generated by pressure nozzles, offering a pathway to improve energy efficiency in spray drying by enabling higher solids loading feedstocks. Furthermore, these insights provide critical guidance for optimizing FEA nozzle designs and process parameters across a range of applications.

Energy efficiency↗

A Verification of Flux Sensitivity Estimates Using the MCNP Tally Perturbation Tool

Nuclear data is commonly used in applications such as nuclear nonproliferation, safeguards, and criticality safety. More specifically, nuclear data is used in predictive simulation codes like the Monte-Carlo N-Particle (MCNP ® ) transport code, Serpent, and similar radiation transport codes. The improvement of nuclear data enables more precise and accurate simulations, which result in higher fidelity designs and reduced operational/procedural costs. Therefore, the improvement of nuclear data is of paramount importance across the nuclear community. Nuclear data is improved and validated through integral benchmark experiments. The design of benchmark experiments is an extensive process; therefore, these experiments are often optimized on multiple characteristics, including sensitivity to the nuclear data, during the design process. Sensitivity is a measure of how much a quantity changes due to changes in independent variables such as experimental configuration. An experimental design that has a larger sensitivity to the nuclear data of interest will have a larger impact on the accuracy and precision of the validated data. Past integral benchmark experiments have primarily used the effective multiplication factor ($k_{eff}$) as the predominant measured quantity; however, experiments designed with other quantities in mind would be able to optimize on validating different areas of the nuclear data. A primary goal of the EUCLID project is to design, constrain, and reduce compensating errors in experiments focused on quantities other than $k_{eff}$ to better validate nuclear data across the board. Currently, there is a capability in MCNP to easily calculate the sensitivity of $k_{eff}$ to specific nuclear data of numerous reactions types and isotopes (KSEN card); however, the sensitivity of other quantities must be estimated in more strenuous manners. For example, the perturbation feature (PERT card) of MCNP can be used to estimate first-order sensitivities of some response in fixed source simulations. A recent announcement revealed that the first- and second-order perturbation features in previous releases of MCNP contained a bug. It was identified that particles were being scored into the wrong energy bin. The bug is in the most recent public release (MCNP6.2); however, a patch has been added to the most up to date version (MCNP6.2.2) that has not been released publicly. A direct comparison of the PERT card results for an F4 (neutron flux averaged over a cell) tally before and after the patch are shown in figure 1. All simulations used in the sensitivity estimates in this report were performed with MCNP6.2.2. This work verifies the patched MCNP perturbation tool by comparing first order sensitivities made using the PERT card to estimates made using manual perturbation of the compact ENDF (ACE) files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modular performance prediction for scientific workflows using Machine Learning

Scientific workflows provide an opportunity for declarative computational experiment design in an intuitive and efficient way. A distributed workflow is typically executed on a variety of resources, and it uses a variety of computational algorithms or tools to achieve the desired outcomes. Such a variety imposes additional complexity in scheduling these workflows on large scale computers. As computation becomes more distributed, insights into expected workload that a workflow presents become critical for effective resource allocation. In this paper, we present a modular framework that leverages Machine Learning for creating precise performance predictions of a workflow. The central idea is to partition a workflow in such a way that makes the task of forecasting each atomic unit manageable and gives us a way to combine the individual predictions efficiently. We recognize a combination of an executable and a specific physical resource as a single module. This gives us a handle to characterize workload and machine power as a single unit of prediction. Overall, our modular technique of creating atomic modules and deployment of longest-path approach to estimate workflow performance, allows the framework to adapt to highly complex nested directed acyclic workflows and scale to new scenarios, since it does not make assumptions of underlying workflow structure. We present performance estimation results of independent workflow modules executed on the XSEDE SDSC Comet cluster using various Machine Learning algorithms. The results provide insights into the behavior and effectiveness of different algorithms in the context of scientific workflow performance prediction.

97 MATHEMATICS AND COMPUTING↗

Experimental study for critical heat flux in 2x2 rod bundles at high pressure conditions

Critical heat flux (CHF) phenomena has been a topic of study for over fifty years yet remains a serious concern across industries and especially in water-cooled nuclear reactor design. CHF data in the high-pressure range is limited, and the effects of bundle geometry and non-uniform heat flux profile are challenging to quantify. In this study, CHF experiments were performed in upward flowing water in a 2 × 2 rod bundle with a cosine profile heat flux. Data were collected between 16.5 and 18 MPa at two mass flux conditions with three inlet subcooling conditions. Under these conditions, average CHF was shown to decrease with increasing pressure. However, pressure had less of an effect than decreasing the inlet subcooling or the mass flux, both of which reduce the CHF value considerably. Of interest, correlations that have been developed for lower pressure continued to predict CHF occurrences with moderate accuracy outside their ranges of validity. Nearly all predicted values were within 20% of experimental values.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗

Mars surface transportation options

As the number of scientific experiments for the surface of Mars grows, the need for effective surface transportation becomes critical. Because of the diversity of the experiments proposed, as well as the desire to explore Mars from the equator to the poles, the optimum surface vehicle configuration is not obvious. Five candidate vehicles are described, with an estimate of their size and performance. In order to maximize the success of a manned Mars mission, it appears that two vehicles should be designed for surface transportation: an advanced long-range rover, and a remotely-piloted airplane.

Jeffrey M Leitner↗

Preliminary Work in Obtaining Site-Directed Mutants of Hen Egg White Lysozyme

Protein crystal growth studies are recognized as a critical endeavor in the field of molecular biotechnology. The scientific applications of this field include the understanding of how enzymes function and the accumulation of accurate information of atomic structures, a key factor in the process of rational drug design. NASA has committed substantial investment and resources to the field of protein crystal growth and has conducted many microgravity protein crystal growth experiments aboard shuttle flights. Crystals grown in space tend to be larger, denser and have a more perfect habit and geometry. These improved properties gained in the microgravity environment of space result largely from the reduction of solutal convection, and the elimination of sedimentation at the growing crystal surface. Shuttle experiments have yielded many large, high quality crystals that are suitable for high resolution X-ray diffraction analysis. Examples of biologically important macromolecules which have been successfully crystallized during shuttle missions include: lysozyme, isocitrate lyase, gamma-interferon, insulin, human serum albumin and canavalin. Numerous other examples are also available. In addition to obtaining high quality crystals, investigators are also interested in learning the mechanisms by which the growth events take place. Crystallization experiments indicate that for the enzyme HEWL, measured growth rates do not follow mathematical models for 2D nucleation and dislocation-led growth of tetragonal protein crystals. As has been suggested by the laboratory of Marc L. Pusey, a possible explanation for the disagreement between observation and data is that HEWL tetraconal crystals form by aggregated units of lysozyme in supersaturated solutions. Surface measurement data was shown to fit very well with a model using an octamer unit cell as the growth unit. According to this model, the aggregation pathway and subsequent crystal growth is described by: monomer < ------ > dimer < ------- > tetramer < ------ > octamer < ------ > higher order. It is believed that multimer aggregation of lysozyme occurs by interaction at specific binding sites on the surface of the protein crystals. If the presence of discrete binding sites and the aggregation hypothesis is true, then it follows that the alteration of the binding site(s) should have significant effect on the measurements obtained during growth experiments. Site-directed mutagenesis allows the specific alteration of proteins by replacement, deletion or addition of specific amino acid residues. This report outlines the approach for this strategy and the progress made thus far toward that end.

Holmes, Leonard D.↗

Planning the Unplanned Experiment: Towards Assessing the Efficacy of Standards for Safety-Critical Software

Safe use of software in safety-critical applications requires well-founded means of determining whether software is fit for such use. While software in industries such as aviation has a good safety record, little is known about whether standards for software in safety-critical applications 'work' (or even what that means). It is often (implicitly) argued that software is fit for safety-critical use because it conforms to an appropriate standard. Without knowing whether a standard works, such reliance is an experiment; without carefully collecting assessment data, that experiment is unplanned. To help plan the experiment, we organized a workshop to develop practical ideas for assessing software safety standards. In this paper, we relate and elaborate on the workshop discussion, which revealed subtle but important study design considerations and practical barriers to collecting appropriate historical data and recruiting appropriate experimental subjects. We discuss assessing standards as written and as applied, several candidate definitions for what it means for a standard to 'work,' and key assessment strategies and study techniques and the pros and cons of each. Finally, we conclude with thoughts about the kinds of research that will be required and how academia, industry, and regulators might collaborate to overcome the noted barriers.

Graydon, Patrick J.↗

Improving Scientific Payload Communication Over Multiple, Low-Capacity Links

Communication is an important part of every airborne science mission. It provides a means for a large group of ground-based scientists to monitor and adjust experiments aboard aircraft that often cannot support a large number of passengers. In some cases, such as unmanned aircraft, communication becomes critical to a successful mission. Existing communication systems require the use of multiple, low-capacity channels, or links, to handle the capacity requirements of the scientists. Current communication solutions attempt to balance performance and reliability, but ultimately suffer from some critical design flaws that limit the ability of the system to handle additional links. We show how adding resources to the current system results in decreased performance and reliability. We explore the use of a new communication protocol, MultiPath Transmission Control Protocol, to make better use of multiple communication links and propose a total system capable of scaling to any number of channels efficiently and dynamically. The tools developed to support and measure this solution are also detailed.

MPTCP↗

Flying Qualities Analysis and Piloted Simulation Testing of a Lift+Cruise Vehicle with Propulsion Failures in Hover and Low-Speed Conditions

The recent emergence of electric-Vertical Take-Off and Landing (eVTOL) vehicles for Urban Air Mobility (UAM) applications has resulted in a wide variety of configurations with unique stability and control characteristics. NASA is currently conducting research to develop conceptual design tools to accelerate public acceptance of these vehicles which includes requirements for safety during failure scenarios. This paper summarizes progress toward a toolbox for predicting flying qualities of eVTOL vehicles during critical propulsion failures that could impact the allowable design of the vehicle geometry or control system. Key topics include unique vulnerabilities of eVTOL/multirotor vehicles to propulsion failures, relevant flying qualities design metrics, and simulation modeling requirements for assessing flying qualities degradation due to failures. Results of a piloted simulation study conducted in the NASA Ames Vertical Motion Simulator (VMS) are presented. The VMS experiment was designed to assess and validate key handling qualities and safety design metrics for propulsion failures. These results show the correlation between control system design requirements and the degradation in handling qualities for various propulsion failures.

George Altamirano↗

Data-Efficient Methods for Determining Flory–Huggins χ Parameters in Multicomponent Polymer Formulations

Polymer formulations are essential in diverse applications including personal care products, coatings, paints, adhesives, and plastic materials. Designing these formulations requires navigating large, complex design spaces, where phase and self-assembly behavior critically impact performance. The Flory–Huggins χ parameter, which quantifies segmental miscibility, is widely used to parametrize the excess free energy of mixing in formulation models. In this work, we introduce two data-efficient, top-down methods for estimating χ parameters using the Random Phase Approximation (RPA): (i) Boundary Nonlinear Regression (Boundary-NLR), which fits theoretical spinodal boundaries to experimental phase boundaries, and (ii) Surrogate Model Inverse Parameter Estimation (SMIPE), which uses a Gaussian Process Classifier to fit sparse phase maps via a surrogate model. Both methods allow rapid parametrization of polymer field-theoretic models without the need for additional experiments. We evaluate these approaches on data sets involving polymer–solvent–nonsolvent ternary mixtures and block copolymer–solvent systems, demonstrating their robustness to experimental noise and their relevance for real-world formulation design.

copolymers↗

Demonstration of Critical Systems for Propellant Production on Mars for Science and Exploration Missions

A Mars hopper has been proposed as a Mars mobility concept that will also demonstrate and advance in-situ resource utilization. The components needed in a Mars propellant production plant have been developed to various levels of technology maturity, but there is little experience with the systems in a Mars environment. Two systems for the acquisition and compression of the thin carbon dioxide atmosphere were designed, assembled, and tested in a Mars environment chamber. A microchannel sorption pump system was able to raise the pressure from 7 Torr to 450 Torr or from 12 Torr to over 700 Torr in two stages. This data now provides information needed to make additional improvements in the sorption pump technology to increase performance, although a system-level analysis might prove that some amount of pre- or post-compression may be a preferred solution. A mini cryofreezer system was also evaluated as an alternative method for carbon dioxide acquisition and compression. Finally, an electrolysis system was tested and successfully demonstrated start-up operation and thermal stability of all components during long-term operation in the chamber.

Linne, Diane L.↗

Free Flight Ground Testing of ADEPT in Advance of the Sounding Rocket One Flight Experiment

The Adaptable Deployable Entry and Placement Technology (ADEPT) project will be conducting the first flight test of ADEPT, titled Sounding Rocket One (SR-1), in just two months. The need for this flight test stems from the fact that ADEPT's supersonic dynamic stability has not yet been characterized. The SR-1 flight test will provide critical data describing the flight mechanics of ADEPT in ballistic flight. These data will feed decision making on future ADEPT mission designs. This presentation will describe the SR-1 scientific data products, possible flight test outcomes, and the implications of those outcomes on future ADEPT development. In addition, this presentation will describe free-flight ground testing performed in advance of the flight test. A subsonic flight dynamics test conducted at the Vertical Spin Tunnel located at NASA Langley Research Center provided subsonic flight dynamics data at high and low altitudes for multiple center of mass (CoM) locations. A ballistic range test at the Hypervelocity Free Flight Aerodynamics Facility (HFFAF) located at NASA Ames Research Center provided supersonic flight dynamics data at low supersonic Mach numbers. Execution and outcomes of these tests will be discussed. Finally, a hypothesized trajectory estimate for the SR-1 flight will be presented.

Smith, B. P.↗

Planned Steady State Irradiation of Characterized Instruments for Nuclear Thermal Rockets Using In-Pile Experiment Apparatus

The development of nuclear rocket technology is critical for the further exploration of extraterrestrial bodies. Nuclear rockets are capable of providing various advantages over current chemical rockets. However, the harsh environment provides a number of challenges regarding instrument performance. Temperature extremes, radiation (reactor and space), and the inability to conduct traditional maintenance activities can lead to a severe degradation in instrument performance. To better understand the effects of radiation on instrumentation, an irradiation campaign has been designed to test a set of instruments provided by a collaborator in the aerospace industry. Details concerning pre-irradiation performance are provided for a future comparison to the irradiated performance. Additionally, the design of the irradiation test is described in detail.

Floyd, Dan↗

Comparison of Computational Predictions of the Mach 0.80 Transonic Truss-Braced Wing Configuration with Experimental Data

The NASA Langley and Ames Research Centers have teamed together for comparisons of computational predictions of the Boeing Mach 0.80Transonic Truss-Braced Wing (TTBW) configuration with a high-speed experimental dataset. The Mach 0.80 TTBW vehicle is a high wing, high aspect ratio configuration, designed for a high lift-to-drag ratio. System studies have predicted significant fuel burn and emissions benefits with the TTBW technology moving toward meeting NASA Subsonic Transport Systems-Level-Metrics. A 4.5% scale Mach 0.80 design TTBW model was recently tested at the NASA Ames Research Center 11-by 11-Foot Transonic Wind Tunnel(11-Ft TWT),providing a valuable dataset to validate computational tools and investigate best practices as risk reduction efforts continue for the development of the advanced TTBW vehicle. The NASA Computational Fluid Dynamics (CFD) team has computed free-air flow solutions on the Mach 0.80 design flight configuration and two wind tunnel configuration variants using the USM3D and LAVA flow solvers. Accurate modeling of the configuration tested in the wind tunnel environment is critical to validating the CFD tools, thus the team has included the internal cavity region and sting in their modeling of the configuration, similar to that tested in the 11-Ft TWT. Overall, the CFD simulations compared well and show similar trends as the corrected experimental data for lift and drag polars. The CFD predicted lift curve is shifted in angle of attack from what was observed in the experiment. The shift in lift also was seen in the pitching moment comparison plots. CFD solutions were computed at constant CL test point values and showed overall very good agreement when comparing constant spanwise cuts of pressure coefficient data on the wing and strut with experimental data. CFD cavity corrections were also investigated using the 11-Ft TWT cavity correction method, similar to that used to correct the wind tunnel data. Results showed some improvement in pitching moment coefficient predictions, and an increase in drag, shifting the data to the right in drag polars, further from the experimental data at lower lift conditions, good agreement near the design CL, and slight improvement at the higher lift conditions.

Transonic Truss-Braced Wing↗

Rapid assessment of the creep rupture life of metals: A model enabling experimental design

Prediction of the creep rupture life of engineering metals is critical for qualification and design of new materials. The use of long-term creep tests and the need to quantify the performance variability in a priori similar systems hinder the rapid creep assessment of a given material. Therefore, it is essential to develop methods that can extrapolate the long-term performance of alloys and the associated variability from short-term experiments. To this end, this study introduces a new model which enables the estimation of the rupture life of a material for a given stress and temperature. This model relies on two components. First, a new relation for the minimum creep rate (MCR) of materials is introduced. It includes a stress dependent stress exponent allowing the model to capture the variation of MCR across a wide range of temperatures and stresses. Second, employing the Monkman-Grant (MG) law, we establish a relation between stress, temperature and creep rupture life. Together, these two elements yield a new closed-form mathematical expression for the Larson Miller parameter as a function of stress and temperature. This expression captures the creep rupture time for many metals (Gr91, Copper, Gr122 and 347H) and compares favorably with alternate empirical approaches. The model is then used to assess the minimum duration of creep rates necessary to qualify the material up to 100000h. Furthermore, it is found that depending on the material system, creep tests as few as five limited to 5000 h for steels (Gr91, Gr122, 347H) and 100 h for copper are sufficient to model creep lifetimes. Finally, using a Bayesian inference-based approach to calibrate the model, we demonstrate that variability in rupture life can be captured via the quantification of the uncertainty in the model parameters and extrapolated from a limited number of short to moderately short creep tests; thereby paving the way for accelerated creep testing.

36 MATERIALS SCIENCE↗

Validation of SAS4A/SASSYS-1 for predicting steady-state single-phase natural circulation

The validation of system analysis codes for nuclear reactor systems is required for the development and application of these computational tools. Designed as a comprehensive system analysis code for advanced nuclear reactors, SAS4A/SASSYS-1 requires validation of its physics model for capturing single-phase natural circulation behavior. To support the validation of SAS4A/SASSYS-1, high-precision experiments are performed capturing steady-state single-phase natural circulation on a scaled facility with comprehensive instrumentation. In this work, dedicated tests are performed quantifying the critical modeling parameters, and a single-phase natural circulation benchmark dataset is obtained with well-documented uncertainty and comprehensive facility description. The validation is then performed against the dataset examining the capability of SAS4A/SASSYS-1 in simulating steady-state single-phase natural circulation. The experimental facility is modeled in the candidate code. Solution verification is performed using Richardson-extrapolation-based estimators which quantify and restrict numerical errors from discretization. Input uncertainty provided by the benchmark dataset is forward propagated through the candidate code, quantifying the output uncertainty in a Monte Carlo approach. The composition of the output uncertainty is also quantified through a variance-based sensitivity analysis. With the uncertainty quantified for each individual condition, a detailed comparison between the simulation results and experimental data is performed covering the whole dataset. The results show consistent agreement for all primary parameters. The current validation activity provides a valuable benchmark dataset for the validation of system analysis codes in capturing single-phase natural circulation and demonstrates satisfactory prediction capability of SAS4A/SASSYS1 for steady-state single-phase natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗