SEARCH · Search NASA

Results for “BOX MODELS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,261 records · Page 70

All sources NASA NTRS DOE OSTI

NASA NTRS1986

SMP: A solid modeling program version 2.0

The Solid Modeling Program (SMP) provides the capability to model complex solid objects through the composition of primitive geometric entities. In addition to the construction of solid models, SMP has extensive facilities for model editing, display, and analysis. The geometric model produced by the software system can be output in a format compatible with existing analysis programs such as PATRAN-G. The present version of the SMP software supports six primitives: boxes, cones, spheres, paraboloids, tori, and trusses. The details for creating each of the major primitive types is presented. The analysis capabilities of SMP, including interfaces to existing analysis programs, are discussed.

Randall, D. P.↗

NASA NTRS1989

Building Mathematical Models Of Solid Objects

Solid Modeling Program (SMP) version 2.0 provides capability to model complex solid objects mathematically through aggregation of geometric primitives (parts). System provides designer with basic set of primitive parts and capability to define new primitives. Six primitives included in present version: boxes, cones, spheres, paraboloids, tori, and trusses. Written in VAX/VMS FORTRAN 77.

Randall, Donald P.↗

NASA NTRSDate not supplied

Prediction of Calcium Oxalate Stone Risk with Interventions

Introduction Mitigations intended to reduce bone mineral loss in-flight also influence the level of renal stone risk to astronauts. Extending a recent study completed by our group [1], we investigate the likely influence of combined fluid intake and Ca excretion mitigation strategies. Methods A computational biochemistry model representing CaOx crystal precipitation, growth, and agglomeration [2] is combined with a probabilistic analysis to predict the in-flight CaOx renal stone incidence risk ratio (IRR) relative to pre-flight values using 1517 astronaut 24-hour urine chemistries. The output of this simulation is used to assess the combined impact of controlling fluid intake and Ca excretion on maintaining IRR < 1.2 for > 95% of the population, a threshold determined from initial analysis of the model output compared to referent populations [1]. Results and Conclusions Figure 1 illustrates the simulated in-flight astronaut population (n=40000) with CaOx IRR > 1.2. The red lines indicate the known clinical risk boundary of each factor, and the white box is considered the area of high combined clinical risk. The simulation and identified risk threshold conform well to the expected clinical risk boundaries. The results, assuming insensible water losses equal or exceed 0.7 L/day, imply mitigations achieve risks similar to pre-flight levels when either Ca < 150 mg/day or fluid volume intake > 3.2 L/day individually, or combined Ca < 200 and fluid volume intake > 2.5 L/day. We continue to investigate similar compounded effects and look to apprise engineering trades by informing relative risk changes during mission design. References [1] D. A. Goodenow-Messman, S. A. Gokoglu, M. Kassemi, and J. Myers, Jerry G., “Characterization of Astronaut CaOx Renal Stone Incidence Rates to Quantify In-flight and Post-flight Relative Risk,” npj Microgravity, in review, 2021. [2] M. Kassemi and D. Thompson, “Prediction of renal crystalline size distributions in space using a PBE analytic model. 1. Effect of microgravity-induced biochemical alterations,” Am. J. Physiol. Physiol., vol. 311, no. 3, pp. F520–F530, Sep. 2016, doi: 10.1152/ajprenal.00401.2015.

Debra A Goodenow↗

DOE OSTI2016

WE-H-207A-03: The Universality of the Lognormal Behavior of [F-18]FLT PET SUV Measurements

Purpose: Log transforming [F-18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F-18]FLT PET SUVs from solid tumors and offers an example of how normal distributions permits analysis of non-independent/correlated measurements. Methods: Forty patients with various metastatic diseases underwent up to six FLT PET/CT scans during treatment. Tumors were identified by nuclear medicine physician and manually segmented. Average uptake was extracted for each patient giving a global SUVmean (gSUVmean) for each scan. The Shapiro-Wilk test was used to test distribution normality. One parameter Box-Cox transformations were applied to each of the six gSUVmean distributions and the optimal transformation was found by selecting the parameter that maximized the Shapiro-Wilk test statistic. The relationship between gSUVmean and a serum biomarker (VEGF) collected at imaging timepoints was determined using a linear mixed effects model (LMEM), which accounted for correlated/non-independent measurements from the same individual. Results: Untransformed gSUVmean distributions were found to be significantly non-normal (p<0.05). The optimal transformation parameter had a value of 0.3 (95%CI: −0.4 to 1.6). Given the optimal parameter was close to zero (which corresponds to log transformation), the data were subsequently log transformed. All log transformed gSUVmean distributions were normally distributed (p>0.10 for all timepoints). Log transformed data were incorporated into the LMEM. VEGF serum levels significantly correlated with gSUVmean (p<0.001), revealing log-linear relationship between SUVs and underlying biology. Conclusion: Failure to account for correlated/non-independent measurements can lead to invalid conclusions and motivated transformation to normally distributed SUVs. The log transformation was found to be close to optimal and sufficient for obtaining normally distributed FLT PET SUVs. These transformations allow utilization of powerful LMEMs when analyzing quantitative imaging metrics.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1976

Ocean foam generation and modeling

A laboratory investigation was conducted to determine the physical and microwave properties of ocean foam. Special foam generators were designed and fabricated, using porous glass sheets, known as glass frits, as the principal element. The glass frit was sealed into a water-tight vertical box, a few centimeters from the bottom. Compressed air, applied to the lower chamber, created ocean foam from sea water lying on the frit. Foam heights of 30 cm were readily achieved, with relatively low air pressures. Special photographic techniques and analytical procedures were employed to determine foam bubble size distributions. In addition, the percentage water content of ocean foam was determined with the aid of a particulate sampling procedure. A glass frit foam generator, with pore diameters in the range 70 - 100 micrometers, produced foam with bubble distributions very similar to those found on the surface of natural ocean foam patches.

Porter, R. A.↗

DOE OSTI2018

Update on the use of Neutron Absorbers for Storage Applications at Y-12

The Y-12 National Security Complex has a high density enriched uranium storage system at the Highly Enriched Uranium Materials Facility (HEUMF) that has been deployed for nearly 10 years. A robust neutron absorber system is provided through the design of Rackable Can Storage Boxes (RCSBs) and their configuration into storage racks. The requirements from ANSI/ANS-8.21, Use of Fixed Neutron Absorbers in Nuclear Facilities outside Reactors, are met with the RCSB and rack system at HEUMF through various design aspects, verification criteria, functional testing, and simulation modeling. Previous publications on a neutron absorber storage system at Y-12 were present at ANS in 2001 and 2002, when the RCSBs were still in a conceptual phase. The publications focused on ongoing studies at the time of what materials worked best for storage applications and how to test those materials, as well the practical design of the unit. The RCSBs have proven to provide a safe, static, and low maintenance storage system, with some minor design issues and several opportunities for future improvement.

42 ENGINEERING↗

NASA NTRS1996

Virtual Reality Simulation of the International Space Welding Experiment

Virtual Reality (VR) is a set of breakthrough technologies that allow a human being to enter and fully experience a 3-dimensional, computer simulated environment. A true virtual reality experience meets three criteria: (1) It involves 3-dimensional computer graphics; (2) It includes real-time feedback and response to user actions; and (3) It must provide a sense of immersion. Good examples of a virtual reality simulator are the flight simulators used by all branches of the military to train pilots for combat in high performance jet fighters. The fidelity of such simulators is extremely high -- but so is the price tag, typically millions of dollars. Virtual reality teaching and training methods are manifestly effective, and we have therefore implemented a VR trainer for the International Space Welding Experiment. My role in the development of the ISWE trainer consisted of the following: (1) created texture-mapped models of the ISWE's rotating sample drum, technology block, tool stowage assembly, sliding foot restraint, and control panel; (2) developed C code for control panel button selection and rotation of the sample drum; (3) In collaboration with Tim Clark (Antares Virtual Reality Systems), developed a serial interface box for the PC and the SGI Indigo so that external control devices, similar to ones actually used on the ISWE, could be used to control virtual objects in the ISWE simulation; (4) In collaboration with Peter Wang (SFFP) and Mark Blasingame (Boeing), established the interference characteristics of the VIM 1000 head-mounted-display and tested software filters to correct the problem; (5) In collaboration with Peter Wang and Mark Blasingame, established software and procedures for interfacing the VPL DataGlove and the Polhemus 6DOF position sensors to the SGI Indigo serial ports. The majority of the ISWE modeling effort was conducted on a PC-based VR Workstation, described below.

Phillips, James A.↗

DOE OSTI2021

A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗

DOE OSTI2013

Adaptive resolution simulation of salt solutions

We present an adaptive resolution simulation of aqueous salt (NaCl) solutions at ambient conditions using the adaptive resolution scheme. Our multiscale approach concurrently couples the atomistic and coarse-grained models of the aqueous NaCl, where water molecules and ions change their resolution while moving from one resolution domain to the other. We employ standard extended simple point charge (SPC/E) and simple point charge (SPC) water models in combination with AMBER and GROMOS force fields for ion interactions in the atomistic domain. Electrostatics in our model are described by the generalized reaction field method. The effective interactions for water–water and water–ion interactions in the coarse-grained model are derived using structure-based coarse-graining approach while the Coulomb interactions between ions are appropriately screened. To ensure an even distribution of water molecules and ions across the simulation box we employ thermodynamic forces. We demonstrate that the equilibrium structural, e.g. radial distribution functions and density distributions of all the species, and dynamical properties are correctly reproduced by our adaptive resolution method. Our multiscale approach, which is general and can be used for any classical non-polarizable force-field and/or types of ions, will significantly speed up biomolecular simulation involving aqueous salt.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Parity-violating inelastic electron-proton scattering at low Q 2 above the resonance region

We report the measurement of the parity-violating asymmetry for the inelastic scattering of electrons from the proton, at $Q^2 = 0.082$ GeV$^2$ and $ W = 2.23$ GeV, above the resonance region. The result $A_{\rm Inel} = - 13.5 \pm 2.0 ({\rm stat}) \pm 3.9 ({\rm syst})$ ppm agrees with theoretical calculations, and helps to validate the modeling of the $\gamma Z$ interference structure functions $F_1^{\gamma Z}$ and $F_2^{\gamma Z}$ used in those calculations, which are also used for determination of the two-boson exchange box diagram ($\Box_{\gamma Z}$) contribution to parity-violating elastic scattering measurements. A positive parity-violating asymmetry for inclusive $\pi^-$ production was observed, as well as positive beam-normal single-spin asymmetry for scattered electrons and a negative beam-normal single-spin asymmetry for inclusive $\pi^-$ production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1977

Interior noise analysis and control for light aircraft

This paper describes experimental and analytical studies of the interior noise of twin-engine, propeller-driven, light aircraft. Experimental results indicate that interior noise levels due to propeller noise can be reduced by reduction of engine rpm at constant airspeed (about 3 dB), by synchronization of the twin engines/propellers (up to 12 dB), and by increasing the distances from propeller tip to fuselage. The analytical model described uses modal methods and incorporates the flat-sided geometrical and skin-stringer structural features of light aircraft. Initial results show good agreement with measured noise transmitted into a rectangular box through a flat panel.

Mixson, J. S.↗

NASA NTRS1994

The evolution of voids in the adhesion approximation

We apply the adhesion approximation to study the formation and evolution of voids in the universe. Our simulations-carried out using 128(exp 3) particles in a cubical box with side 128 Mpc-indicate that the void spectrum evolves with time and that the mean void size in the standard Cosmic Background Explorer Satellite (COBE)-normalized cold dark matter (CDM) model with H(sub 50) = 1 scals approximately as bar D(z) = bar D(sub zero)/(1+2)(exp 1/2), where bar D(sub zero) approximately = 10.5 Mpc. Interestingly, we find a strong correlation between the sizes of voids and the value of the primordial gravitational potential at void centers. This observation could in principle, pave the way toward reconstructing the form of the primordialpotential from a knowledge of the observed void spectrum. Studying the void spectrum at different cosmological epochs, for spectra with a built in k-space cutoff we find that the number of voids in a representative volume evolves with time. The mean number of voids first increases until a maximum value is reached (indicating that the formation of cellular structure is complete), and then begins to decrease as clumps and filaments erge leading to hierarchical clustering and the subsequent elimination of small voids. The cosmological epoch characterizing the completion of cellular structure occurs when the length scale going nonlinear approaches the mean distance between peaks of the gravitaional potential. A central result of this paper is that voids can be populated by substructure such as mini-sheets and filaments, which run through voids. The number of such mini-pancakes that pass through a given void can be measured by the genus characteristic of an individual void which is an indicator of the topology of a given void in intial (Lagrangian) space. Large voids have on an average a larger measure than smaller voids indicating more substructure within larger voids relative to smaller ones. We find that the topology of individual voids is strongly epoch dependent, with void topologies generally simplifying with time. This means that as voids grow older they become progressively more empty and have less structure within them. We evaluate the genus measure both for individual voids as well as for the entire ensemble of voids predicted by CDM model. As a result we find that the topology of voids when taken together with the void spectrum is a very useful statistical indicator of the evolution of the structure of the universe on large scales.

Sahni, Varun↗

NASA NTRS2023

Orbital Debris Quarterly News, June 2023

Inside - DAS Release - Recent Advances in Modeling Hollow Objects During Reentry - Two Years of Space Traffic: Current Trends in New Payloads and Debris in Orbit - Overview of ORDEM Web Application Features - Workshop Report - Upcoming Meetings - Space Missions and Satellite Box Score

Heather Cowardin↗

DOE OSTI2017

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Machine learning and algebraic approaches towards complete matter spectra in 4d F-theory

Motivated by engineering vector-like (Higgs) pairs in the spectrum of 4d F-theory compactifications, we combine machine learning and algebraic geometry techniques to analyze line bundle cohomologies on families of holomorphic curves. To quantify jumps of these cohomologies, we first generate 1.8 million pairs of line bundles and curves embedded in dP 3 , for which we compute the cohomologies. A white-box machine learning approach trained on this data provides intuition for jumps due to curve splittings, which we use to construct additional vector-like Higgs-pairs in an F-Theory toy model. We also find that, in order to explain quantitatively the full dataset, further tools from algebraic geometry, in particular Brill-Noether theory, are required. Using these ingredients, we introduce a diagrammatic way to express cohomology jumps across the parameter space of each family of matter curves, which reflects a stratification of the F-theory complex structure moduli space in terms of the vector-like spectrum. Furthermore, these insights provide an algorithmically efficient way to estimate the possible cohomology dimensions across the entire parameter space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Microfluidic Fabrication of Nanoparticles Based on Ethyl Acrylate-Functionalized Chitosan for Adsorption of Methylene Blue from Aqueous Solutions

The adsorption of nanoparticle (NP)-based adsorbents especially those made of polymers to remove dyes as toxic substances from pollutants is yet remained as a critical issue. The objective of this work was to prepare microfluidic (MF) fabrication of NPs based on ethyl acrylate (EA)-functionalized chitosan (CS) for methylene blue (MB) dye removal from aqueous solutions. For this purpose, a series of experiments such as FTIR, SEM alongside DLS, and UV–vis spectrophotometry were carried out to investigate the physicochemical properties of the samples. The FTIR spectra showed that the amine (–NH{sub 2}) and hydroxyl (–OH) groups on CS structure were replaced with EA, appropriately. The SEM and DLS results depicted that EA-functionalized CS NPs fabricated using MF technique had uniform shapes, and the diameters as small as 70 nm compared to those samples produced via bulk mixing (BM) method (~ 300 nm). Moreover, the surface charge of MF-assisted CS NPs after functionalization exhibited the lower zeta potential value (~ + 11) than that of samples based on BM (~ + 14) due to occurring the laminar flow through the micro-channels embedded in the MF chip, leading to an increase in the MB adsorption. Subsequently, at the optimized amounts of the dye concentration (89.12 mg L{sup −1}), the adsorbent concentration (1.38 g L{sup −1}), and pH (10.58) by means of Box-Behnken design (BBD) method, the maximum percentage of MB removal by the use of MF-fabricated EA-functionalized CS NPs was 98.4%. By fitting the obtained adsorption data to the isotherm models such as Lagmuir, Freundlich, and Temkin, it has been found that the adsorption mechanism followed the Langmuir model (maximum capacity of the adsorption 384.61 mg/g), which assumed a monolayer coverage of MB molecules as adsorbates over a homogeneous adsorbent surface.

36 MATERIALS SCIENCE↗

DOE OSTI2017

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

Hohman, Frederick M.↗