A Refrigerant Charge Prediction Method Based on Pump Down Operation Validated Using Residential and Commercial Heat Pump Systems
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Li, Zhenning↗
SEARCH · Engineering Papers
Results for “validation method”
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Prediction of space sickness in astronauts from preflight fluid, electrolyte, and cardiovascular variables and Weightless Environmental Training Facility (WETF) training
Nine preflight variables related to fluid, electrolyte, and cardiovascular status from 64 first-time Shuttle crewmembers were differentially weighted by discrimination analysis to predict the incidence and severity of each crewmember's space sickness as rated by NASA flight surgeons. The nine variables are serum uric acid, red cell count, environmental temperature at the launch site, serum phosphate, urine osmolality, serum thyroxine, sitting systolic blood pressure, calculated blood volume, and serum chloride. Using two methods of cross-validation on the original samples (jackknife and a stratefied random subsample), these variables enable the prediction of space sickness incidence (NONE or SICK) with 80 percent sickness and space severity (NONE, MILD, MODERATE, of SEVERE) with 59 percent success by one method of cross-validation and 67 percent by another method. Addition of a tenth variable, hours spent in the Weightlessness Environment Training Facility (WETF) did not improve the prediction of space sickness incidences but did improve the prediction of space sickness severity to 66 percent success by the first method of cross-validation of original samples and to 71 percent by the second method. Results to date suggest the presence of predisposing physiologic factors to space sickness that implicate fluid shift etiology. The data also suggest that prior exposure to fluid shift during WETF training may produce some circulatory pre-adaption to fluid shifts in weightlessness that results in a reduction of space sickness severity.
Simanonok, K.↗
Subsurface Trend Analysis domains for the northern Gulf of Mexico
Geologic domains for the northern Gulf of Mexico derived using the Subsurface Trend Analysis (STA) method. The domains were postulated using geologic province, lithologic, and structural information and validated using statistical methods. Publication detailing the STA method: Rose, K., Bauer, J.R., and Mark-Moser, M. (2020) Subsurface trend analysis, a multi-variate geospatial approach for subsurface evaluation and uncertainty reduction, Interpretation, vol. 8, issue 1 https://library.seg.org/doi/abs/10.1190/int-2019-0019.1 Detailed discussion of domain formation and analysis: Mark-Moser, M., Miller, R., Bauer, J., Rose, K., and C. Disenhof. 2018, Analysis of Subsurface Reservoir Properties Using a Novel Geospatial Approach, Offshore Gulf of Mexico. NETL-TRS-2018 https://edx.netl.doe.gov/dataset/detailed-analysis-of-geospatial-trends-of-hydrocarbon-accumulations-offshore-gulf-of-mexico
geology↗
Comparison of measured and predicted flight effects on high-bypass coaxial jet exhaust noise
A semi-empirical model for predicting the noise generated by conventional-velocity profile coaxial jets is compared with full scale flight data and model scale simulated flight data for high bypass nozzles. The prediction model was shown to agree with small scale static data for primary jet velocities from 215 to 795 m/s for a wide range of area, temperature, and velocity ratios between streams. However, there were insufficient model nozzle, simulated flight data available at that time to permit validation of the flight effects prediction. The comparisons presented demonstrate that the prediction method is also valid in flight.
Stone, J. R.↗
VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS
This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.
97 MATHEMATICS AND COMPUTING↗
Verification and Validation of Progressive Damage and Failure Analysis Methods for Intralaminar Failure Modes in Thermoplastic Composites
Current progressive damage and failure analysis (PDFA) methods were developed around thermoset material systems and their physical behavior. However, the applicability of these analysis methods has not been evaluated for use in modeling thermoplastic material systems. As part of the Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project sponsored by NASA, intralaminar failure characterization was completed on a thermoplastic material system, AS4D/PEKK-FC, with off-axis tension (OAT) and off-axis compression (OAC) testing. The experiments were able to capture matrix non-linear shear behavior and the failure envelope of the material system. Two PDFA methods, LS-DYNA MAT299 and NASA’s CompDam-DGD, were then employed to simulate individual coupon behavior and simulation results were compared to published verification and validation guidelines from the CMH-17 crashworthiness working group. The results found that the two modeling methods provided suitable representation of material behavior of thermoplastics.
PDFA↗
Verification and Validation of Progressive Damage and Failure Analysis Methods for Intralaminar Failure Modes in Thermoplastic Composites
Current progressive damage and failure analysis (PDFA) methods were developed around thermoset material systems and their physical behavior. However, the applicability of these analysis methods has not been evaluated for use in modeling thermoplastic material systems. As part of the Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project sponsored by NASA, intralaminar failure characterization was completed on a thermoplastic material system, AS4D/PEKK-FC, with off-axis tension (OAT) and off-axis compression (OAC) testing. The experiments were able to capture matrix non-linear shear behavior and the failure envelope of the material system. Two PDFA methods, LS-DYNA MAT299 and NASA’s CompDam-DGD, were then employed to simulate individual coupon behavior and simulation results were compared to published verification and validation guidelines from the CMH-17 crashworthiness working group. The results found that the two modeling methods provided suitable representation of material behavior of thermoplastics.
PDFA↗
A Pattern-Recognition-Based Ensemble Data Imputation Framework for Sensors from Building Energy Systems
Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important. There are two key research gaps for missing sensor data imputation in buildings: the lack of customized and automated imputation methodology, and the difficulty of the validation of data imputation methods. In this paper, a framework is developed to address these two gaps. First, a validation data generation module is developed based on pattern recognition to create a validation dataset to quantify the performance of data imputation methods. Second, a pool of data imputation methods is tested under the validation dataset to find an optimal single imputation method for each sensor, which is termed as an ensemble method. The method can reflect the specific mechanism and randomness of missing data from each sensor. The effectiveness of the framework is demonstrated by 18 sensors from a real campus building. The overall accuracy of data imputation for those sensors improves by 18.2% on average compared with the best single data imputation method.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Data-Driven Digital Twin for Reliability Assessment of DC/DC Buck Converter
In commercial applications, the operation of DC/DC converters significantly impacts overall system performance and long-term reliability. This study introduces a data-driven digital twin (DT) approach for estimating critical degradation parameters of DC/DC BUCK converter under steady-state condition. Initially, a circuit-level MATLAB/Simulink digital model (DM C ) is refined against a hardware prototype’s switching model dataset using offline particle swarm optimization. The optimized digital model’s steady-state response is then verified with its average model response while varying the duty and load. Subsequently, degradation profiles are imposed on the inductor, capacitor, MOSFET in the DMC. A large dataset is generated from this model, allowing training, validation, and testing of machine learning (ML) models for component health regression tasks. The proposed method employs random forest ML models, achieving impressive regression results with a squared R value as high as 0.99978 and a root mean square error of 4.2× 10 –6 . The method is further validated on a medium power level DC/DC BUCK prototype with varying load conditions, and includes the analysis of MOSFET’s on-resistance under degradation conditions. This data-driven DT method shows promise for identifying parasitic degradation and ohmic loss parameters, enhancing converter reliability assessments in a non-invasive, generalized, and computationally efficient manner.
14 SOLAR ENERGY↗
[Quantification and monitoring of vascular resistance in the lower limbs by the Doppler method (animal model)]
The object of this study was to define and validate a non-invasive method of evaluation and monitoring of vascular resistances in the leg. Blood flow velocity was measured by Doppler ultrasound in an animal model (ewe) with similar blood flow characteristics in the lower limb as man and allowing access to the required invasive measurements for validation of the method (pressure and flow). Vascular resistances distal to the measuring point (femoral, for example) were assessed using the resistance index R = D/S, S being the peak systolic deflection and D that of diastolic reflux of the Doppler spectral analysis of flow in the femoral artery. The values and variations of this resistance index were compared with the vascular resistances calculated from measurements of pressure and flow at the point of Doppler sampling and expressed in mmHg/ml/min. Femoral flow was measured by Doppler ultrasound (Doppler-echo), and mean pressure by an arterial catheter introduced into the abdominal aorta. Compression of the lower limb veins induced a venous return resulting in a reduction of cardiac output and femoral flow. During compression, femoral flow decreased by an average of 29% (p < 0.001) although mean pressure and heart rate did not change significantly. The femoral resistance index (Rf) increased by an average of 37.5% (p < 0.01) and vascular resistances increased by 45.9% (p < 0.01). Injection of 1 mg adrenaline induced peripheral vasoconstriction with an increase in blood pressure and a decrease in heart rate and femoral flow.(ABSTRACT TRUNCATED AT 250 WORDS).
Non-NASA Center↗
Integrating Human Factors into Crew Exploration Vehicle Design
With NASA's new Vision for Exploration to send humans beyond Earth orbit, it is critical to consider the human as a system that demands early and continuous user involvement, and an iterative prototype/test/redesign process. Addressing human-system interface issues early on can be very cost effective even cost reducing when performed early in the design and development cycle. To achieve this goal within Crew Exploration Vehicle (CEV) Project Office, human engineering (HE) team is formed. Key tasks are to apply HE requirements and guidelines to hardware/software, and provide HE design, analysis and evaluation of crew interfaces. Initial activities included many practice-orientated evaluations using low-fidelity CEV mock-ups. What follows is a description of such evaluations that focused on a HE requirement regarding Net Habitable Volume (NHV). NHV is defined as the total remaining pressurized volume available to on-orbit crew after accounting for the loss of volume due to deployed hardware and structural inefficiencies which decrease functional volume. The goal of the NHV evaluations was to develop requirements providing sufficient CEV NHV for crewmembers to live and perform tasks in support of mission goals. Efforts included development of a standard NHV calculation method using computer models and physical mockups, and crew/ stakeholder evaluations. Nine stakeholders and ten crewmembers participated in the unsuited evaluations. Six crewmembers also participated in a suited evaluation. The mock-up was outfitted with volumetric representation of sub-systems such as seats, and stowage bags. Thirteen scenarios were developed to represent mission/crew tasks and considered to be primary volume drivers (e.g., suit donning) for the CEV. Unsuited evaluations included a structured walkthrough of these tasks. Suited evaluations included timed donning of the existing launch and entry suit to simulate a contingency scenario followed by doffing/ stowing of the suits. All mockup evaluations were videotaped. Structured questionnaires were used to document user interface issues and volume impacts of layout configuration. Computer model and physical measures of the NHV agreed within 1 percent. This included measurement of the gross habitable volume, subtraction of intrusive volumes, and other non-habitable spaces. Calculation method developed was validated as a standard means of measuring NHV, and was recommended as a verification method for the NHV requirements. Evaluations confirmed that there was adequate volume for unsuited scenarios and suit donning/ doffing activity. Seats, suit design stowage and waste hygiene system noted to be critical volume drivers. The low-fidelity mock-up evaluations along with human modeling analysis generated discussions that will lead to high-level systems requirements and human-centered design decisions. This approach allowed HE requirements and operational concepts to evolve in parallel with engineering system concepts and design requirements. As the CEV design matures, these evaluations will continue and help with design decisions, and assessment, verification and validation of HE requirements.
Whitmore, Mihriban↗
Aerodynamic loads near cranks, apexes, and tips of thin, lifting wings in incompressible flow
The calculation of the incompressible and irrotational flow in the vicinity of tips and corners of thin, lifting wings is considered. It is shown that the important characteristics of the flow are governed by an eigenvalue problem, which is nonlinear at the trailing edge because of the shed wake (assumed to be in the wing plane). A new solution method was devised because either the existing methods were not valid for the trailing edge case or they would have required excessive amounts of computer time. The new method, which is fundamentally different than the previous ones, was used to calculate solutions for a number of cases, including some for which correct answers had not previously been obtained. Two of these solutions were used to determine the validity of drag and leading-edge-suction distributions near the tips of a delta wing and a swept wing as calculated by using both the vortex lattice method and a kernel function method. The calculations for the swept wing resolved the question of whether or not the induced drag should be zero at the wing tip.
Medan, R. T.↗
Validation of k eff Calculations for Extended BWR Burnup Credit
The US Nuclear Regulatory Commission and consensus standards recommend validation of the numerical methods used in criticality safety analyses. This validation requires the comparison of computational results with measurements of physical systems which are neutronically similar to those used in the safety analysis being performed. To this end, this document examines the methods available to generate sensitivity data to help identify systems similar to spent boiling- water reactor (BWR) fuel in a flooded spent nuclear fuel transportation or storage cask. A large number of critical benchmark experiments are surveyed using sensitivity/uncertainty (S/U) techniques to assess their applicability to BWR burnup credit (BUC) beyond the burnup of peak reactivity. Multiple burnups of BWR assemblies are considered herein, as well as the actinide-only (AO) and actinide-and-major-fission-product (AFP) isotope sets. Sample validations are completed for representative application models to demonstrate that appropriate validation is possible and to indicate the bias and bias uncertainty values expected for related applications.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Quantifying EGS Reservoir Complexity with an Integrated Geophysical Approach-Improved Resolution Ambient Seismic Noise Interferometry
The primary goal of the project was met, as improved resolution (from kilometers to tens/hundreds of meters and to a depth of at least 3 km) was added to the seismic interferometry-estimated parameters relative to the work reported in AltaRock Energy Inc. (2014) for the Dixie Valley Geothermal Wellfield. A procedure for initial fault identification, using seismic interferometry, was developed. The project team further improved, and applied a new, cost-effective, and non-invasive exploration method, developed and validated since 2010, during two previous experiments, at Dixie Valley and Soda Lake, Nevada. The method, initially designed for hydrothermal exploration, was adapted to EGS exploration conditions, which require deeper crustal information. Regions of elevated energy for both the 2-7 Hz and 5-15 Hz frequency bands are located above intersections of multiple faults. Thus, an unprecedented, innovative seismic field deployment and ambient seismic noise and signal processing were successfully used to estimate crustal structure and to identify fault locations at depths up to 3 km, at a cost per kilometer of survey that in some cases may be as much as ten times less than the cost of a controlled-source survey. Based on valid and useful seismic data collected and analyzed during Phase I, in Phase II the team has further quantified statistically the advantage of using seismic analysis, in combination with other geological and geophysical techniques, for EGS target identification. A power spectral density analysis of the passive-seismic empirical Green’s functions reveals significantly higher power recorded over the exploration area at the power plant, and in the drilling area, near the BB station 10201, especially on the horizontal components. In this study, the most important relationship observed during the prior report, namely the one between velocity and temperature was explored. The areas that show anomalously high predicted temperature in the geostatistics occur where multiple faults intersect. Not surprisingly, such areas span between the Dixie Valley range front fault and the basin-ward Piedmont faults, in the vicinity of numerous wells. These locations also fall in the area of high EGS favorability from the prior 2014 study. The anomalies also coincide with the high power spectral density values. The result of altering all favorability criteria for the new data reached a maximum of 1/8th of a point and were not large enough to change any favorability value reported in the 2014 study. The new data reinforce the results obtained from the previous 2014 study. The current high-resolution ambient seismic noise project provided excellent results in defining faults in the wellfield. As such the identification of known faults by the project demonstrated the utility of this method for identifying faults at an exploration stage in geothermal development. Such fault identification, while extremely useful in exploration investigation, has not added sufficient new data for the generation of significantly different DVGW favorability maps in the current project. We believe the cost savings of our passive-seismic technique for EGS, over common industry active-source survey techniques, may have a minimum of 30%, and a maximum of 90%. There are many significant non-cost benefits of passive seismic surveys. Our passive-source method provides an environmentally-friendly seismic survey with minimal to negligible impacts. The economic benefit is greater EGS project feasibility.
15 GEOTHERMAL ENERGY↗
Verification and Validation Process for Progressive Damage and Failure Analysis Methods in the NASA Advanced Composites Consortium
The Advanced Composites Consortium is a US Government/Industry partnership supporting technologies to enable timeline and cost reduction in the development of certified composite aerospace structures. A key component of the consortium's approach is the development and validation of improved progressive damage and failure analysis methods for composite structures. These methods will enable increased use of simulations in design trade studies and detailed design development, and thereby enable more targeted physical test programs to validate designs. To accomplish this goal with confidence, a rigorous verification and validation process was developed. The process was used to evaluate analysis methods and associated implementation requirements to ensure calculation accuracy and to gage predictability for composite failure modes of interest. This paper introduces the verification and validation process developed by the consortium during the Phase I effort of the Advanced Composites Project. Specific structural failure modes of interest are first identified, and a subset of standard composite test articles are proposed to interrogate a progressive damage analysis method's ability to predict each failure mode of interest. Test articles are designed to capture the underlying composite material constitutive response as well as the interaction of failure modes representing typical failure patterns observed in aerospace structures.
Wanthal, Steven↗
Formal methods and their role in digital systems validation for airborne systems
This report is based on one prepared as a chapter for the FAA Digital Systems Validation Handbook (a guide to assist FAA certification specialists with advanced technology issues). Its purpose is to explain the use of formal methods in the specification and verification of software and hardware requirements, designs, and implementations; to identify the benefits, weaknesses, and difficulties in applying these methods to digital systems used in critical applications; and to suggest factors for consideration when formal methods are offered in support of certification. The presentation concentrates on the rationale for formal methods and on their contribution to assurance for critical applications within a context such as that provided by DO-178B (the guidelines for software used on board civil aircraft); it is intended as an introduction for those to whom these topics are new.
Rushby, John↗
Advanced Reactor Development: Gas-Cooled Reactor First Quarter 2023 Report
ART Program First Quarter report for 2023. Entries for Fuels Development and Qualification, High Temperature Materials Development, Graphite Development and Qualification, and Design Methods Modeling and Validation.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Advanced modeling and simulation of research reactors using dynamic mode decomposition
Full text of publication follows. Due to the ever-increasing safety requirements, the current trend of nuclear reactor analysis is shifting towards high-fidelity multi-physics models, which have a very high computational cost and modelling complexity. As the cost of even a single model run makes it impossible to analyse the behaviour and performance of these models on large-scale commercial plants, it has become even more significant to provide suitable benchmarks to validate and test them extensively. In this sense, research reactors offer a promising solution for the initial validation of high-fidelity models, as they are significantly smaller than commercial reactors and their characteristics are well known. In particular, the reactors of the TRIGA family have been used to assess and validate models and methods for Generation-IV designs, as they have some similar features (such as the dominance of natural convection as cooling mechanism and the difficulties in performing sub-channel analysis using standard codes). Still, the computational requirements of high-fidelity models make them unsuitable for real-time analysis, even following their assessment on research reactors. In this sense, Model Order Reduction (MOR) techniques give an additional strategy to reduce the computational cost of high-fidelity models (whilst preserving sufficient accuracy). In particular, this work focuses on Dynamic Mode Decomposition (DMD), a non-intrusive MOR technique that aims at representing models with explicit temporal dynamics by extracting the time-varying characteristics and the governing structures based only on a set of available data, thus without needing any underlying knowledge of the governing equations. In addition, DMD also computes a low-dimensional surrogate of the dynamic matrix of the system, making it suited for stability analysis and real-time evaluations. This work focuses on the application and validation of the DMD method on the Computational Fluid-Dynamics (CFD) model TRIGA Mark II reactor, also discussing in detail the potentiality of this algorithm as an advanced modelling tool for nuclear reactor analysis. (author)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗