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At least 325 records · Page 18

Development and Validation of a Process Model and Open-Source Process Simulator for Microalgae-Based Tertiary Phosphorus Recovery

Microalgae-based tertiary wastewater treatment has the potential to meet stringent effluent phosphorus limits, with the added benefit of producing a marketable feedstock. However, the lack of validated mechanistic models and their implementation in process simulators have limited the adoption of this technology. In this study, an updated lumped pathway metabolic model (Phototrophic-Mixotrophic Process Model, PM 2 ), including both photoautotrophic and heterotrophic metabolisms of microalgae, was developed to predict effluent phosphorus concentration and biomass yield in response to dynamic influent and varying environmental conditions. The model was implemented in QSDsan – an open-source, Python-based design and simulation platform – for robust simulation under uncertainty. A global sensitivity analysis was performed to prioritize model parameters for calibration. The model was then calibrated and validated using batch experimental data and 45 days of continuous online monitoring data from a full-scale (568 m 3 ·d -1 ) microalgae-based tertiary wastewater treatment plant (EcoRecover process). In particular, along with dynamic influent composition, temperature and light intensity data with diel variation were provided as model inputs to reflect the microalgal behavior under day-night cycling. Overall, the QSDsan-based microalgae process simulator was able to predict effluent phosphorus within 0.02–0.04 mg-P·L -1 , while also capturing the general trends of state variables according to nutrient availability.

Lumped pathway metabolic model↗

Conjugating binary systems for spacecraft thermal control. Appendix C: Aeroassist Flight Experiment Carrier Vehicle preliminary stress analysis

An assessment of the static strength of the Aeroassist Flight Experiment (AFE) Carrier Vehicle is presented. The Carrier Vehicle is the structural component which provides the mounting platform for the experiments, on-board computers, batteries, and other black boxes. In addition, the Solid Rocket Motor (SRM), the Thrusters, and the Aerobrake are all attached directly to the Carrier Vehicle. The basic approach in this analysis was to develop a NASTRAN Finite Element Model as a parallel effort to the preliminary design, and to use the internal loads from this model to perform the stress analysis. The NASTRAN method of Inertial Relief was employed. This method involves either specifying a set of CG (center of gravity) accelerations or applying forces at the CG and representing the Carrier Vehicle and all its mounted devices with the proper stiffness and mass properties.

Ingram, J. E.↗

Low-Earth Orbit Flight Test of an Inflatable Decelerator Modeling and Reconstruction

The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) mission was a flight test performed on November 10, 2022. LOFTID is an 6 meter diameter Hypersonic Inflatable Aerodynamic Decelerator (HIAD) that is stowed for launch as a secondary payload, inflated in space, and separated from launch vehicle before conducting entry, descent, and landing (EDL).The main objective of the flight test was to demonstrate EDL at scale using HIAD technology at flight conditions relevant for future Earth and Mars missions. LOFTID successfully inflated and separated with a spin rate of 18 deg/s, landed within 1 hour on-parachute off the coast of Hawaii, and was successfully recovered. LOFTID re-entered Earth’s atmosphere at 8 km/s, achieved peak deceleration of 9 Gs and peak heat rate of 40 W/cm2, and demonstrated angle-of-attack stability throughout entirety of flight. On-board instrumentation provided flight data, which was saved onto an ejectable data recorder that was ejected at 18 km and successfully recovered. Despite the loss of inertial measurement unit data, techniques were developed to reconstruct the estimated flight performance as described in this paper. This paper presents the trajectory analysis, aerodynamics modeling, and reconstructed flight performance of the LOFTID re-entry vehicle.

Rohan G Deshmukh↗

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

CFD modeling of turbulent air flow in self-heated gyroid TPMS structures: Thermal-hydraulic performance and validation

The application of mathematically derived geometries, such as triply periodic minimal surface (TPMS) lattices, has garnered significant interest across various fields, including the nuclear sector, due to their superior thermal-hydraulic characteristics for heat transfer compared to traditional plain or finned tubes. Here, this study validates a computational fluid dynamics (CFD) model, evaluates different turbulence models and CFD model settings, and performs uncertainty quantification to provide a comprehensive analysis. Despite extensive research on CFD modeling of TPMS lattices, such as gyroid and diamond geometries, there is a notable lack of publicly available literature providing comprehensive details on numerical analysis aspects, including convergence and methodological best practices. This study embarks on a benchmark analysis of a gyroid geometry to evaluate its thermal-hydraulic performance under turbulent flow conditions and scrutinize various CFD model configurations. The main contributions of this work include validating the CFD model, assessing and comparing different turbulence models, and enhancing pressure drop and temperature prediction capabilities. The results aim to support the development of methodologies needed to benchmark and enhance numerical analysis techniques for TPMS lattices. This work seeks to complement the existing body of knowledge, support the development of TPMS reactor concepts, and improve best practices for CFD modeling of TPMS lattices, ultimately advancing methodologies to support future applications in this domain.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Post2 End-to-End Descent and Landing Simulation for ALHAT Design Analysis Cycle 2

The ALHAT project is an agency-level program involving NASA centers, academia, and industry, with a primary goal to develop a safe, autonomous, precision-landing system for robotic and crew-piloted lunar and planetary descent vehicles. POST2 is used as the 6DOF descent and landing trajectory simulation for determining integrated system performance of ALHAT landing-system models and lunar environment models. This paper presents updates in the development of the ALHAT POST2 simulation, as well as preliminary system performance analysis for ALDAC-2 used for the testing and assessment of ALHAT system models. The ALDAC-2 POST2 Monte Carlo simulation results have been generated and focus on HRN model performance with the fully integrated system, as well performance improvements of AGNC and TSAR model since the previous design analysis cycle

Davis, Jody L.↗

Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases

Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. Here, the results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity analysis of thermal contact conductance modeling to inform MiniFuel irradiation capsule designs

The MiniFuel irradiation platform has been developed by Oak Ridge National Laboratory as a flexible, high-throughput separate effects testing capability within the High Flux Isotope Reactor (HFIR). Finite element thermal models are relied upon to design MiniFuel experiments to achieve a specific time-averaged irradiation temperature for experimental objectives. A previous study identified that uncertainty in the component heat generation rates and thermal contact conductance (TCC) model are the most significant contributors to predicted fuel temperature variance. To address both sources of uncertainty, this work performs sensitivity analysis on the TCC model to identify high-impact, high-uncertainty parameters that contribute to fuel temperature variance. The TCC model is analyzed in increasing detail, first using a standalone Python code, then again after coupling Python to the BISON fuel performance code. Furthermore, the parameters with the largest contributions to fuel temperature variance which can be reduced through design changes are identified as the initial subcapsule gas pressure, contact pressure between the fuel and dish, and the effective surface roughness of the interface. A set of design recommendations for future capsule designs has been established and applied to reduce the previously quantified average fuel temperature uncertainty ranges of ± 40 °C in the HFIR vertical experiment facilities (VXF) and ± 80 °C in the removable beryllium (RB) reflector to approximately ± 32 °C and ± 53 °C, respectively. This equates to a 21 % and 33 % reduction in the uncertainty range of the average fuel temperature for VXF and RB, respectively.

BISON↗

Thermal analysis of conceptual designs for GPHS/FPSE power systems of 250 We and 500 We

Thermal analyses were performed for two distinct configurations of a proposed space nuclear power system which combines General Purpose Heat Source (GPHS) modules with the state of the art Free-Piston Stirling Engines (FPSEs). The two configurations correspond to systems with power levels of 250 and 500 W(sub e). The 250 W(sub e) GPHS/FPSE power system utilizes four GPHS modules and one FPSE, and the 500 W(sub e) contains eight GPHS modules and two FPSEs. The configurations of the systems and the bases for selecting the configurations are described. Brief introductory sections are included to describe the GPHS modules and free piston Stirling engines. The primary focus of the thermal analyses is on the temperature of the iridium fuel clad within the GPHS modules. A design goal temperature of 1573 K was selected as the upper limit for the fuel clad during normal operating conditions. The basis for selecting this temperature limit is discussed in detail. Results obtained from thermal analysis of the 250 W(sub e) GPHS/FPSE power system indicate fuel clad temperatures which slightly exceed the design goal temperature of 1573 K. The results are considered favorable due to the numerous conservative assumptions used in developing the thermal model and performing the thermal analysis. To demonstrate the effects of the conservatism, a brief sensitivity analysis is performed in which a few of the key system parameters are varied to determine their effect on the fuel clad temperatures. It is concluded that thermal analysis of a more detailed thermal model would be expected to yield fuel clad temperatures below the design foal temperature limiy 1573 K.

Mccomas, Thomas J.↗

EVA Performance Prediction

Astronaut physical performance capabilities in micro gravity EV A or on planetary surfaces when encumbered by a life support suit and debilitated by a long exposure to micro gravity will be less than unencumbered pre flight capabilities. The big question addressed by human factors engineers is: what can the astronaut be expected to do on EVA or when we arrive at a planetary surface? A second question is: what aids to performance will be needed to enhance the human physical capability? These questions are important for a number of reasons. First it is necessary to carry out accurate planning of human physical demands to ensure that time and energy critical tasks can be carried out with confidence. Second it is important that the crew members (and their ground or planetary base monitors) have a realistic picture of their own capabilities, as excessive fatigue can lead to catastrophic failure. Third it is important to design appropriate equipment to enhance human sensory capabilities, locomotion, materials handling and manipulation. The evidence from physiological research points to musculoskeletal, cardiovascular and neurovestibular degradation during long duration exposure to micro gravity . The evidence from the biomechanics laboratory (and the Neutral Buoyancy Laboratory) points to a reduction in range of motion, strength and stamina when encumbered by a pressurized suit. The evidence from a long history of EVAs is that crewmembers are indeed restricted in their physical capabilities. There is a wealth of evidence in the literature on the causes and effects of degraded human performance in the laboratory, in sports and athletics, in industry and in other physically demanding jobs. One approach to this challenge is through biomechanical and performance modeling. Such models must be based on thorough task analysis, reliable human performance data from controlled studies, and functional extrapolations validated in analog contexts. The task analyses currently carried out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

Peacock, Brian↗

User's Manual for the FE/NETL Onshore CO 2 EOR Cost Model, Version 1

This user's manual describes the conceptual and mathematical basis for the FE/NETL Onshore CO 2 EOR Cost Model (a Fortran program). The model performs a cash flow analysis to estimate the cost of implementing CO 2 EOR using supercritical CO 2 by incorporating oil field performance outputs for a pattern from the FE/NETL CO 2 Prophet Model (available on NETL's website along with its associated user's manuals under the Collection Name: FE/NETL CO 2 Prophet Model) and implementing patterns to develop an oil field for CO 2 EOR. The model calculates capital costs, operation and maintenance costs, and financing costs. The user’s manual also describes how to run the FE/NETL Onshore CO 2 EOR Cost Model, along with the model’s file structure, inputs and outputs. The FE/NETL Onshore CO 2 EOR Cost Model is available on NETL's website under the Collection Name: FE/NETL Onshore CO 2 EOR Cost Model.

54 ENVIRONMENTAL SCIENCES↗

6DOF Testing of the SLS Inertial Navigation Unit

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). Because the navigation architecture for the SLS Block 1 vehicle is a purely inertial system, the accuracy of the achieved orbit relative to mission requirements is very sensitive to initial alignment accuracy. The assessment of this sensitivity and many others via simulation is a part of the SLS Model-Based Design and Model-Based Requirements approach. As a part of the aforementioned, 6DOF Monte Carlo simulation is used in large part to develop and demonstrate verification of program requirements. To facilitate this and the GN&C flight software design process, an SLS-Program-controlled Design Math Model (DMM) of the SLS INS was developed by the SLS Navigation Team. The SLS INS model implements all of the key functions of the hardware-namely, GCA, inertial navigation, and FDIR (Fault Detection, Isolation, and Recovery)-in support of SLS GN&C design requirements verification. Despite the strong sensitivity to initial alignment, GCA accuracy requirements were not verified by test due to program cost and schedule constraints. Instead, the system relies upon assessments performed using the SLS INS model. In order to verify SLS program requirements by analysis, the SLS INS model is verified and validated against flight hardware. In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Geohagan, Kevin↗

A Test Generation Framework for Distributed Fault-Tolerant Algorithms

Heavyweight formal methods such as theorem proving have been successfully applied to the analysis of safety critical fault-tolerant systems. Typically, the models and proofs performed during such analysis do not inform the testing process of actual implementations. We propose a framework for generating test vectors from specifications written in the Prototype Verification System (PVS). The methodology uses a translator to produce a Java prototype from a PVS specification. Symbolic (Java) PathFinder is then employed to generate a collection of test cases. A small example is employed to illustrate how the framework can be used in practice.

Goodloe, Alwyn↗

Predicting Pilot Performance in Off-Nominal Conditions: A Meta-Analysis and Model Validation

Pilot response to off-nominal (very rare) events represents a critical component to understanding the safety of next generation airspace technology and procedures. We describe a meta-analysis designed to integrate the existing data regarding pilot accuracy of detecting rare, unexpected events such as runway incursions in realistic flight simulations. Thirty-five studies were identified and pilot responses were categorized by expectancy, event location, and whether the pilot was flying with a highway-in-the-sky display. All three dichotomies produced large, significant effects on event miss rate. A model of human attention and noticing, N-SEEV, was then used to predict event noticing performance as a function of event salience and expectancy, and retinal eccentricity. Eccentricity is predicted from steady state scanning by the SEEV model of attention allocation. The model was used to predict miss rates for the expectancy, location and highway-in-the-sky (HITS) effects identified in the meta-analysis. The correlation between model-predicted results and data from the meta-analysis was 0.72.

Wickens, C.D.↗

ABF Past Accomplishments - TEA/LCA

The Integrated Analysis task in the Agile BioFoundry (ABF) conducts techno-economic analysis (TEA) and life cycle assessment (LCA) to quantify the economics and environmental impacts of bioprocesses under development. The team from Argonne National Laboratory (ANL) and the National Renewable Energy Laboratory (NREL) develops TEA and LCA models of selected compound targets and hosts of interest to the ABF in an effort to provide an analysis-based foundation to the R&D. To date, the Integrated Analysis task has performed process modeling and analyses on multiple pairings of bioproducts and hosts, centered around major metabolic "beachheads" and "exemplar" molecules chosen for each of the metabolic pathways of interest. This presentation provides an overview of the approach used for TEA and LCA in the ABF and of the progress, outcomes, and impacts of TEA and LCA to support ABF goals, with a focus towards developing bio-based products that are both environmentally and economically viable.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Solar Array Verification Analysis Tool (SAVANT) Developed

Modeling solar cell performance for a specific radiation environment to obtain the end-of-life photovoltaic array performance has become both increasingly important and, with the rapid advent of new types of cell technology, more difficult. For large constellations of satellites, a few percent difference in the lifetime prediction can have an enormous economic impact. The tool described here automates the assessment of solar array on-orbit end-of-life performance and assists in the development and design of ground test protocols for different solar cell designs. Once established, these protocols can be used to calculate on-orbit end-of-life performance from ground test results. The Solar Array Verification Analysis Tool (SAVANT) utilizes the radiation environment from the Environment Work Bench (EWB) model developed by the NASA Lewis Research Center s Photovoltaic and Space Environmental Effects Branch in conjunction with Maxwell Technologies. It then modifies and combines this information with the displacement damage model proposed by Summers et al. (ref. 1) of the Naval Research Laboratory to determine solar cell performance during the course of a given mission. The resulting predictions can then be compared with flight data. The Environment WorkBench (ref. 2) uses the NASA AE8 (electron) and AP8 (proton) models of the radiation belts to calculate the trapped radiation flux. These fluxes are integrated over the defined spacecraft orbit for the duration of the mission to obtain the total omnidirectional fluence spectra. Components such as the solar cell coverglass, adhesive, and antireflective coatings can slow and attenuate the particle fluence reaching the solar cell. In SAVANT, a continuous slowing down approximation is used to model this effect.

Bailey, Sheila G.↗

Build-Up Approach to Updating the Mock Quiet Spike Beam Model

When a new aircraft is designed or a modification is done to an existing aircraft, the aeroelastic properties of the aircraft should be examined to ensure the aircraft is flight worthy. Evaluating the aeroelastic properties of a new or modified aircraft can include performing a variety of analyses, such as modal and flutter analyses. In order to produce accurate results from these analyses, it is imperative to work with finite element models (FEM) that have been validated by or correlated to ground vibration test (GVT) data, Updating an analytical model using measured data is a challenge in the area of structural dynamics. The analytical model update process encompasses a series of optimizations that match analytical frequencies and mode shapes to the measured modal characteristics of structure. In the past, the method used to update a model to test data was "trial and error." This is an inefficient method - running a modal analysis, comparing the analytical results to the GVT data, manually modifying one or more structural parameters (mass, CG, inertia, area, etc.), rerunning the analysis, and comparing the new analytical modal characteristics to the GVT modal data. If the match is close enough (close enough defined by analyst's updating requirements), then the updating process is completed. If the match does not meet updating-requirements, then the parameters are changed again and the process is repeated. Clearly, this manual optimization process is highly inefficient for large FEM's and/or a large number of structural parameters. NASA Dryden Flight Research Center (DFRC) has developed, in-house, a Mode Matching Code that automates the above-mentioned optimization process, DFRC's in-house Mode Matching Code reads mode shapes and frequencies acquired from GVT to create the target model. It also reads the current analytical model, as we11 as the design variables and their upper and lower limits. It performs a modal analysis on this model and modifies it to create an updated model that has similar mode shapes and frequencies as those of the target model. The Mode Matching Code output frequencies and modal assurance criteria (MAC) values that allow for the quantified comparison of the updated model versus the target model. A recent application of this code is the F453 supersonic flight testing platform, NASA DFRC possesses a modified F-15B that is used as a test bed aircraft for supersonic flight experiments. Traditionally, the finite element model of the test article is generated. A GVT is done on the test article ta validate and update its FEM. This FEM is then mated to the F-15B model, which was correlated to GVT data in fall of 2004, A GVT is conducted with the test article mated to the aircraft, and this mated F-15B/ test article FEM is correlated to this final GVT.

Herrera, Claudia Y.↗