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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Developing a space-filling mixture experiment design when the components are subject to linear and nonlinear constraints

This article presents a case study of developing a space-filling design (SFD) for a constrained mixture experiment when the experimental region is specified by single-component constraints (SCCs), linear multiple-component constraints (LMCCs), and nonlinear multiple-component constraints (NMCCs). Traditional methods and software for designing constrained mixture experiments with SCCs and LMCCs (using either optimal design or SFD approaches) are not directly applicable because of the NMCCs. A SFD algorithm in the JMP software was modified to accommodate the nonlinear MCCs; the modification is described in this article. The case study involves high-level waste (HLW) glass that is subject to the formation of nepheline crystals as the glass cools. This can significantly reduce the durability of HLW glass (which is undesirable). The goal of the study was to develop a SFD for the HLW glass compositional region where nepheline may form, and generate data for modeling nepheline formation as a function of HLW glass composition. The HLW glass composition region was specified in terms of eight components with SCCs, two LMCCs, and two NMCCs. The NMCCs were based on a nonlinear logistic regression model for a binary-response nepheline response that was developed from previous data. This article discusses the HLW glass example, the constraints specifying the experimental composition region, and how an existing algorithm for generating SFDs was modified to accommodate the NMCCs. The methodology discussed in this article can be applied to any example in which the experimental region is specified by one or more nonlinear constraints in addition to linear constraints on mixture components and/or non-mixture variables.

Mixture experiment, space-filling experimental des↗
DOE OSTI2013

Development of a Rubber-Based Product Using a Mixture Experiment: A Challenging Case Study

Many products used in daily life are made by blending two or more components. The properties of such products typically depend on the relative proportions of the components. Experimental design, modeling, and data analysis methods for mixture experiments provide for efficiently determining the component proportions that will yield a product with desired properties. This article presents a case study of the work performed to develop a new rubber formulation for an o-ring (a circular gasket) with requirements specified on 10 product properties. Each step of the study is discussed, including: 1) identifying the objective of the study and requirements for properties of the o-ring, 2) selecting the components to vary and specifying the component constraints, 3) constructing a mixture experiment design, 4) measuring the responses and assessing the data, 5) developing property-composition models, 6) selecting the new product formulation, and 7) confirming the selected formulation in manufacturing. The case study includes some challenging and new aspects, which are discussed in the article.

Full-cubic mixture model↗
DOE OSTI2015

Designing a mixture experiment when the components are subject to a nonlinear multiple-component constraint

This article presents a case study of developing an experimental design for a constrained mixture experiment when the experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directly applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this article. The case study involves a 15-component nuclear waste glass example in which SO3 is one of the components. SO3 has a solubility limit in glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO3 solubility limit had previously been modeled by a partial quadratic mixture (PQM) model expressed in the relative proportions of the 14 other components. The PQM model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This article discusses the waste glass example and how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study.

Low-activity waste↗
DOE OSTI2018

Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions

A paper by Foglio Bonda et al. published previously in this journal (2016, Vol. 83, pp. 175–183) discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (Z ave ). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). This commentary addresses some errors and other issues in the previous paper, and also discusses an improved model relating proportions of ITZ, TW20, and E5 to Z ave . The improved model contains six of the 10 terms in the full-cubic mixture model, which were selected using a different cross-validation procedure than used in the previous paper. In conclusion, compared to the four-term model presented in the previous paper, the improved model fit the data better, had excellent cross-validation performance, and the predicted Z ave of a validation point was within model uncertainty of the measured value.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Nonlinear Logistic Regression Mixture Experiment Modeling for Binary Data Using Dimensionally Reduced Components

This article presents and illustrates an approach using nonlinear logistic regression for modeling binary response data from a mixture experiment when the components can be partitioned into groups used to form dimensionally-reduced pseudocomponents (DRPs). A DRP is a linear combination of the components in a group, where the linear combinations over all groups are normalized so that the DRP proportions sum to unity. Nonlinear logistic regression is required because, after normalization of the linear combinations, the model expressed in terms of the DRPs is nonlinear in the parameters that specify the linear combinations. A method for obtaining nonparametric tolerance limits on the probability of a “success” for the binary response variable using a bootstrap approach is also presented. Having three DRPs enables viewing data and modeling results on a ternary plot even though there may be many more than three mixture components. A real database, involving whether or not nepheline crystals form in simulated nuclear waste glass after cooling, is used to illustrate the nonlinear logistic regression modeling and nonparametric tolerance limit approaches when there are three DRPs.

Waste glass, Nepheline, Mixture experiment, Logist↗
NASA NTRS2012

Supercritical Water Mixture (SCWM) Experiment

The subject presentation, entitled, Supercritical Water Mixture (SCWM) Experiment, was presented at the International Space Station (ISS) Increment 33/34 Science Symposium. This presentation provides an overview of an international collaboration between NASA and CNES to study the behavior of a dilute aqueous solution of Na2SO4 (5% w) at near-critical conditions. The Supercritical Water Mixture (SCWM) investigation, serves as important precursor work for subsequent Supercritical Water Oxidation (SCWO) experiments. The SCWM investigation will be performed in DECLICs High Temperature Insert (HTI) for the purpose of studying critical fluid phenomena at high temperatures and pressures. The HTI includes a completely sealed and integrated test cell (i.e., Sample Cell Unit SCU) that will contain approximately 0.3 ml of the aqueous test solution. During the sequence of tests, scheduled to be performed in FY13, temperatures and pressures will be elevated to critical conditions (i.e., Tc = 374C and Pc = 22 MPa) in order to observe salt precipitation, precipitate agglomeration and precipitate transport in the presence of a temperature gradient without the influences of gravitational forces. This presentation provides an overview of the motivation for this work, a description of the DECLIC HTI hardware, the proposed test sequences, and a brief discussion of the scientific research objectives.

Hicks, Michael C.↗
DOE OSTI2020

A Collection of More than 900 Gas Mixture Adsorption Experiments in Porous Materials from Literature Meta-Analysis

Information on mixture adsorption equilibrium is vital in developing adsorption-based separation processes. Because measuring mixture adsorption is more difficult than measuring single-component adsorption, far more data of the latter kind are available. Previous efforts to compile experimental mixture adsorption data for gases have given data sets with at most a few dozen examples. Here, we report the results of systematic literature meta-analysis that produced a data set of more than 900 gas mixture adsorption experiments. This collection includes data from 125 different binary mixtures including 60 different molecular species and information from 333 different adsorbents. We refer to this data set as the Binary adsorption ISOtherm ExperimeNtal 2020 (BISON-20) Database. Because the BISON-20 data set enormously expands the number and variety of experimental results for binary gas adsorption that are readily available, it will be a useful resource for future efforts in developing new materials or processes for gas separations. As initial applications of the BISON-20 data set, we show how identifying replicate measurements can be used to assess the reliability of binary adsorption data, how the accuracy of Ideal Adsorbed Solution Theory (IAST) can be systematically tested using experimental data, and how trends in selectivity for gas separations across many materials can be examined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

Supercritical Water Mixture (SCWM) Experiment in the High Temperature Insert-Reflight (HTI-R)

Current research on supercritical water processes on board the International Space Station (ISS) focuses on salt precipitation and transport in a test cell designed for supercritical water. This study, known as the Supercritical Water Mixture Experiment (SCWM) serves as a precursor experiment for developing a better understanding of inorganic salt precipitation and transport during supercritical water oxidation (SCWO) processes for the eventual application of this technology for waste management and resource reclamation in microgravity conditions. During typical SCWO reactions any inorganic salts present in the reactant stream will precipitate and begin to coat reactor surfaces and control mechanisms (e.g., valves) often severely impacting the systems performance. The SCWM experiment employs a Sample Cell Unit (SCU) filled with an aqueous solution of Na2SO4 0.5-w at the critical density and uses a refurbished High Temperature Insert, which was used in an earlier ISS experiment designed to study pure water at near-critical conditions. The insert, designated as the HTI-Reflight (HTI-R) will be deployed in the DECLIC (Device for the Study of Critical Liquids and Crystallization) Facility on the International Space Station (ISS). Objectives of the study include measurement of the shift in critical temperature due to the presence of the inorganic salt, assessment of the predominant mode of precipitation (i.e., heterogeneously on SCU surfaces or homogeneously in the bulk fluid), determination of the salt morphology including size and shapes of particulate clusters, and the determination of the dominant mode of transport of salt particles in the presence of an imposed temperature gradient. Initial results from the ISS experiments will be presented and compared to findings from laboratory experiments on the ground.

salts↗
DOE OSTI2013

Optimum Tolerance Design Using Component-Amount and Mixture-Amount Experiments

One type of tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface (RS) designs and models to solve this type of tolerance design problem. In this article, component-amount (CA) and mixture-amount (MA) approaches are proposed as more appropriate for solving this type of tolerance design problem. The advantages of the CA and MA approaches over the RS approach are discussed. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling, and optimization) are illustrated using real examples.

component-amount experiment↗
NASA NTRS1984

Spontaneous ignition characteristics of gaseous hydrocarbon-air mixtures

Experiments are conducted to determine the spontaneous ignition delay times of gaseous propane, kerosine vapor, and n-heptane vapor in mixtures with air, and oxygen-enriched air, at atmospheric pressure. Over a range of equivalence ratios from 0.2 to 0.8 it is found that ignition delay times are sensibly independent of fuel concentration. However, the results indicate a strong dependence of delay times on oxygen concentration. The experimental data for kerosine and propane demonstrate very close agreement with the results obtained previously by Mullins and Lezberg respectively.

Freeman, G.↗
NASA NTRS1977

Double-discharge stabilization of supersonic CO laser mixtures

Experiments have been conducted to study the applicability of a CW double-discharge stabilization scheme under conditions appropriate for high-energy lasers in supersonic flows. Steady arc-free volume discharges have been produced in a Mach 3 supersonic-flow test cavity using an auxiliary discharge to stabilize the main discharge at low-current densities in N2 and He/CO mixtures. A significant result is the lack of observed plasma E/N changes in response to auxiliary-discharge current changes. Also, where glow discharges were obtained, the energy loading achieved was less than the threshold required for laser operation.

Srinivasan, G.↗
DOE OSTI2016

Additive effects of levonorgestrel and ethinylestradiol on brain aromatase (cyp19a1b) in zebrafish specific in vitro and in vivo bioassays

Estrogens and progestins are widely used in combination in human medicine and both are present in aquatic environment. Despite the joint exposure of aquatic wildlife to estrogens and progestins, very little information is available on their combined effects. In the present study we investigated the effect of ethinylestradiol (EE2) and Levonorgestrel (LNG), alone and in mixtures, on the expression of the brain specific ER-regulated cyp19a1b gene. For that purpose, recently established zebrafish-derived tools were used: (i) an in vitro transient reporter gene assay in a human glial cell line (U251-MG) co-transfected with zebrafish estrogen receptors (zfERs) and the luciferase gene under the control of the zebrafish cyp19a1b gene promoter and (ii) an in vivo bioassay using a transgenic zebrafish expressing GFP under the control of the zebrafish cyp19a1b gene promoter (cyp19a1b-GFP). Concentration-response relationships for single chemicals were modeled and used to design the mixture experiments following a ray design. The results from mixture experiments were analyzed to predict joint effects according to concentration addition and statistical approaches were used to characterize the potential interactions between the components of the mixtures (synergism/antagonism). We confirmed that some progestins could elicit estrogenic effects in fish brain. In mixtures, EE2 and LNG exerted additive estrogenic effects both in vitro and in vivo, suggesting that some environmental progestin could exert effects that will add to those of environmental (xeno-)estrogens. Moreover, our zebrafish specific assays are valuable tools that could be used in risk assessment for both single chemicals and their mixtures. - Highlights: • Combined effects of EE2 and LNG were assessed on ER-dependent cyp19a1b expression. • EE2 and LNG alone induced brain aromatase in zebrafish specific bioassays. • Experimental ray design allowed complete concentration-response surfaces modeling. • EE2 and LNG exerted additive effects on brain aromatase in radial glial cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Insights into co-pyrolysis of polyethylene terephthalate and polyamide 6 mixture through experiments, kinetic modeling and machine learning

The non-isothermal pyrolysis of polyethylene terephthalate (PET), polyamide 6 (PA6), and their mixtures was studied in a thermogravimetric analyzer at different heating rates. Temperature of maximum decomposition (T max ) decreased by 25–45 °C and 35–55 °C for the PET:PA6 mixtures (3:1, 1:1, 1:3) compared to PET and PA6, respectively. The kinetic analysis was initially carried out using isoconversional method. However, the dependency of activation energy on conversion was observed for the co-pyrolysis of PET and PA6 that suggested the occurrence of multi-step reactions in the mixtures. Distributed activation energy model (DAEM) was used in this study to describe the multistep reactions occurring during pyrolysis of PET:PA6 mixtures. Here, in this work, a four-parallel reaction DAEM was developed to describe the pyrolysis kinetics of PET:PA6 mixtures. The apparent mean activation energies (E o ) for PET, PA6, and mixtures varied in the range of 244–255, 140–215, and 138–255 kJ mol –1 , respectively. The mass loss profiles of PET and PA6 mixtures were also modeled using artificial neural network (ANN). Out of 155 ANN models, the best prediction was made by ANN511 with R 2 greater than 0.997 for both test and unseen data. The interaction effects observed through TGA experiments and subsequent kinetic analysis were further assessed in terms of product composition using analytical pyrolysis coupled with gas chromatograph/mass spectrometer (Py-GC/MS). Co-pyrolysis of PET and PA6 resulted in the formation of new aromatic compounds with nitrogen-containing functional groups, which were not detected when PET or PA6 were pyrolyzed individually.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Experimental Design for Hanford Low-Activity Waste Glasses with High Waste Loading

This report discusses the development of an experimental design for the initial phase of the Hanford low-activity waste (LAW) enhanced glass study. This report is based on a manuscript written for an applied statistics journal. Appendices A, B, and E include additional information relevant to the LAW enhanced glass experimental design that is not included in the journal manuscript. The glass composition experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC involving 15 LAW glass components. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directly applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this report. One of the glass components, SO 3 , has a solubility limit in glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO 3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO 3 solubility limit had previously been modeled by a partial quadratic mixture model expressed in the relative proportions of the 14 other components. The partial quadratic mixture model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This report describes how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study. A layered design consists of points on an outer layer, and inner layer, and a center point. There were 18 outer-layer glasses chosen using optimal experimental design software to augment 147 existing glass compositions that were within the LAW glass composition experimental region. Then 13 inner-layer glasses were chosen with the software to augment the existing and outer-layer glasses. The experimental design was completed by a center-point glass, a Vitreous State Laboratory glass, and replicates of the center point and Vitreous State Laboratory glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Investigation of Dalton and Amagat’s laws for gas mixtures with shock propagation

Dalton's and Amagat's laws (also known as the law of partial pressures and the law of partial volumes respectively) are two well-known thermodynamic models describing gas mixtures. We focus our current research on determining the suitability of these models in predicting effects of shock propagation through gas mixtures. Experiments are conducted at the Shock Tube Facility at the University of New Mexico (UNM). The gas mixture used in these experiments consists of approximately 50% sulfur hexafluoride (SF6) and 50% helium (He) by mass. Fast response pressure transducers are used to obtain pressure readings both before and after the shock wave; these data are then used to determine the velocity of the shock wave. Temperature readings are obtained using an ultra-fast mercury cadmium telluride (MCT) infrared (IR) detector, with a response time on the order of nanoseconds. Coupled with a stabilized broadband infrared light source (operating at 1500 K), the detector provides pre- and post-shock line-of-sight readings of average temperature within the shock tube, which are used to determine the speed of sound in the gas mixture. Paired with the velocity of the shock wave, this information allows us to determine the Mach number. Our experimental results are compared with theoretical predictions of Dalton's and Amagat's laws to determine which one is more suitable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Two-phase flow and heat transfer under low gravity

Spacelab experiment to investigate two-phase flow patterns under gravity uses a water-air mixture experiment. Air and water are circulated through the system. The quality or the mixture or air-water is controlled. Photographs of the test section are made and at the same time pressure drop across the test section is measured. The data establishes a flow regime map under reduced gravity conditions with corresponding pressure drop correlations. The test section is also equipped with an electrical resistance heater in order to allow a flow boiling experiment to be carried out using Freon II. High-speed photographs of the test section are used to determine flow patterns. The temperature gradient and pressure drop along the duct can be measured. Thus, quality change can be measured, and heat transfer calculated.

Walter Frost↗
NASA NTRS1995

STS-94 Day 14 Highlights

On this fourteenth day of the STS-94 mission, the flight crew, Cmdr. James D. Halsell, Jr., Pilot Susan L. Still, Payload Cmdr, Janice E. Voss, Mission Specialists Michael L. Gernhardt and Donald A. Thomas, and Payload Specialists Gregory T. Linteris and Roger K. Crouch continue to focus on Columbia's Microgravity Science Laboratory mission. The seven astronauts work around the clock on two shifts supporting the more than 30 experiments in the Spacelab module. Work in the laboratory includes plant experiment and protein crystal growth status checks as well as work in the glovebox on the Coarsening in Solid-Liquid Mixtures experiment.

Source record↗