Results for “BAG MODEL” — Page 7

DOE OSTI2012

Preliminary results of a precision measurement of the neutron d2: Probing the Lorentz color force

The quantity d{sub 2}, related to a twist-three matrix element, is a measure of the average restoring Lorentz color force experienced by a quark inside a polarized nucleon after it is struck by a virtual photon in electron Deep Inelastic Scattering (DIS). With its information encoded in both spin structure functions g{sub 1} and g{sub 2} in the quark valence region at large Bjorken x, this confining local force is a result of the remnant di-quark system attracting the struck quark. While bag-and chiralsoliton-model calculations for the neutron d{sub 2} are consistent with those of lattice Quantum Chromodynamics (QCD), current experimental data differ by approximately two standard deviations from those theoretical results. To address this issue, the experiment E06-014 was carried out from February to March of 2009 at Jefferson Lab. It consisted of measuring doublespin asymmetries and the total cross section by scattering a longitudinally polarized electron beam from a longitudinally or transversely polarized {sup 3}He target, allowing for the extraction of the neutron d{sub 2}. The experiment covered excitation energies in the resonance and DIS valence quark regions. Preliminary cross sections and asymmetries will be presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1970

Development of a portable life support system and emergency life support pack

The design, development, and fabrication of a feasibility model of a breathing bag life support system for extravehicular activity are discussed. The breathing vest and back pack portable life support system contains connectors which allow external water and gas supply. At a metabolic rate of 2000 BTU per hour, the two low pressure bottles provide 27 minutes of breathing gas for a total filled system weight of 30.5 pounds.

Source record↗

NASA NTRS1974

Scale drogue parachute model

Drogue parachute models, pilot parachute models, and their deployment bags were fabricated incorporating recommended design changes. These changes are described in detail.

Source record↗

NASA NTRS2009

Modeling and Simulation of the Second-Generation Orion Crew Module Air Bag Landing System

Air bags were evaluated as the landing attenuation system for earth landing of the Orion Crew Module (CM). Analysis conducted to date shows that airbags are capable of providing a graceful landing of the CM in nominal and off-nominal conditions such as parachute failure, high horizontal winds, and unfavorable vehicle/ground angle combinations, while meeting crew and vehicle safety requirements. The analyses and associated testing presented here surround a second generation of the airbag design developed by ILC Dover, building off of relevant first-generation design, analysis, and testing efforts. In order to fully evaluate the second generation air bag design and correlate the dynamic simulations, a series of drop tests were carried out at NASA Langley s Landing and Impact Research (LandIR) facility in Hampton, Virginia. The tests consisted of a full-scale set of air bags attached to a full-scale test article representing the Orion Crew Module. The techniques used to collect experimental data, develop the simulations, and make comparisons to experimental data are discussed.

Timmers, Richard B.↗

NASA NTRSDate not supplied

Recommendations For Developing Space Suit Integrated Food Systems and Delivering Nutrition Before, During, and After Lunar Eva

INTRODUCTION Artemis missions will include a higher tempo and frequency of extravehicular activities (EVAs) than any previous space program. Because of the physical demands expected from the crew, future space suit designs are required to incorporate nutritional support to the astronauts during lunar surface EVAs lasting longer than 4 hours. The purpose of this project was to provide recommendations to aid the development of an in-suit system that can adequately, safely, and acceptably deliver nutrition to a crewmember while confined to a space suit during EVA. METHODS Physiological, logistical, and engineering aspects of potential in-suit nutrition approaches were assessed through literature reviews, assessments of commercial off the shelf (COTS) foods, suit volumetric modeling, and feedback from subject matter experts and crewmembers. Key driving factors in the development of in-suit nutrition requirements included how much and what type of nutrition should be included, what food formulations are appropriate and safe, what are inherent limitations of space suits, what are the potential risks to the crewmember in the suit, and what practices and preferences from astronauts should be considered. Design references were conceptualized and assessed for strengths and limitations as potential in-suit nutrition systems for surface EVA. RESULTS Acute exogenous energy demands vary greatly depending on activity intensity and duration, and partial energy replenishment (i.e., 60–80 kcal∙hr-1 of EVA, or 460–680 kcal for EVAs lasting up to 8 hours) during activities could improve performance, safety, and recovery. COTS foods capable of providing these energy requirements exist; however, no COTS foods have been identified that pass NASA flight standards for microbiological safety and stability. In-suit nutrition delivery design references that were considered included in-suit concepts for a prefilled drink bag, a hydratable drink bag, and a solid food stick. In addition, a helmet feed port concept was considered for use with drink bags external to the suit. Volumetric models of the in-suit drink bag concepts, based on xEMU dimensions, indicate challenges of fitting formulations > 200 ml (equating to approximately 200 kcal). Astronaut feedback on the four concepts indicated that despite some individual preferences for inclusion of solid foods and helmet port designs, the prefilled drink bag concept was the most preferred. A prefilled drink bag can only be used if food safety and stability can be ensured, possibly requiring advancements in food delivery hardware. CONCLUSION The ability to meet the increased need for nutrition during surface EVAs through provision of nutrients in the suited configuration would benefit overall crew health, performance, and morale, and thus increase the likelihood of mission success. It is recommended that in-suit nutrition capabilities provide at least 400–600 kcal within the suit during EVAs lasting > 4 hours and that suit designs include a dedicated volume for food grade nutrition systems. The developed food system should either allow for 1) installation of prefilled (sealed sterile) liquid nutrition in the suit and provide a mechanism to break the seal at the time that consumption is desired or 2) demonstrate that the unsealed food product shelf life allows for safe consumption after at least 12 hours of EVA.

E L Dillon↗

NASA NTRSDate not supplied

Recommendations for Developing Space Suit Integrated Food Systems and Delivering Nutrition Before, During, and After Lunar EVA

INTRODUCTION Artemis missions will include a higher tempo and frequency of extravehicular activities (EVAs) than any previous space program. Because of the physical demands expected from the crew, future space suit designs are required to incorporate nutritional support to the astronauts during lunar surface EVAs lasting longer than 4 hours. The purpose of this project was to provide recommendations to aid the development of an in-suit system that can adequately, safely, and acceptably deliver nutrition to a crewmember while confined to a space suit during EVA. METHODS Physiological, logistical, and engineering aspects of potential in-suit nutrition approaches were assessed through literature reviews, assessments of commercial off the shelf (COTS) foods, suit volumetric modeling, and feedback from subject matter experts and crewmembers. Key driving factors in the development of in-suit nutrition requirements included how much and what type of nutrition should be included, what food formulations are appropriate and safe, what are inherent limitations of space suits, what are the potential risks to the crewmember in the suit, and what practices and preferences from astronauts should be considered. Design references were conceptualized and assessed for strengths and limitations as potential in-suit nutrition systems for surface EVA. RESULTS Acute exogenous energy demands vary greatly depending on activity intensity and duration, and partial energy replenishment (i.e., 60–80 kcal∙hr-1 of EVA, or 460–680 kcal for EVAs lasting up to 8 hours) during activities could improve performance, safety, and recovery. COTS foods capable of providing these energy requirements exist; however, no COTS foods have been identified that pass NASA flight standards for microbiological safety and stability. In-suit nutrition delivery design references that were considered included in-suit concepts for a prefilled drink bag, a hydratable drink bag, and a solid food stick. In addition, a helmet feed port concept was considered for use with drink bags external to the suit. Volumetric models of the in-suit drink bag concepts, based on xEMU dimensions, indicate challenges of fitting formulations > 200 ml (equating to approximately 200 kcal). Astronaut feedback on the four concepts indicated that despite some individual preferences for inclusion of solid foods and helmet port designs, the prefilled drink bag concept was the most preferred. A prefilled drink bag can only be used if food safety and stability can be ensured, possibly requiring advancements in food delivery hardware. CONCLUSION The ability to meet the increased need for nutrition during surface EVAs through provision of nutrients in the suited configuration would benefit overall crew health, performance, and morale, and thus increase the likelihood of mission success. It is recommended that in-suit nutrition capabilities provide at least 400–600 kcal within the suit during EVAs lasting > 4 hours and that suit designs include a dedicated volume for food grade nutrition systems. The developed food system should either allow for 1) installation of prefilled (sealed sterile) liquid nutrition in the suit and provide a mechanism to break the seal at the time that consumption is desired or 2) demonstrate that the unsealed food product shelf life allows for safe consumption after at least 12 hours of EVA.

space suit↗

DOE OSTI2018

Algae Farm Cost Model: Considerations for Photobioreactors

Cost estimates and assumptions for a vertical hanging-bag type photobioreactor (PBR) system are reported here for a preliminary model developed to elucidate major cost drivers and opportunities for reducing the costs of algae cultivation. The design inputs and assumptions for this system are described in the report. A baseline case is presented, and alternative cases with differing areal algal productivities are used to compare to an open-pond case. The baseline algae production cost is estimated to be 1,137/short ton (st) algae, on an ash-free dry weight (AFDW) basis (2016 US$). Sensitivity analyses probe the areal productivity, support structure cost, and PBR bag replacement cost and life as significant impact factors affecting the system cost. A preliminary comparison of the PBR system and an open pond system is also developed to indicate the cost difference between these two systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Restoration increases bee abundance and richness but not pollination in remnant and post-agricultural woodlands

Human land use, including agriculture, is a leading contributor to declining biodiversity worldwide and can leave long-lasting legacies on ecosystems after cessation. Ecological restoration is an approach to mitigate these impacts. However, little is known about how animal communities and plant–animal interactions respond to the combined effects of land-use legacies and restoration. We investigated how restoration and agricultural history affect bee (Hymenoptera: Apoidea: Anthophila) communities and pollination function. In 27 paired remnant (no history of agriculture) and post-agricultural longleaf pine (Pinus palustris Mill.) woodlands, we established 4–10 1-ha plots (126 total) and experimentally restored half of them, while the other half were left as unrestored controls. Restoration was accomplished through canopy thinning which reinstates open savanna-like conditions. We collected bees in each plot using a combination of bowl trapping and standardized netting transects. Thinning increased bee abundance by 169% and bee richness by 110%, but agricultural land use had no effect on these variables. Bee community composition was affected by restoration and was marginally affected by agricultural history. To measure pollination function, we conducted a sentinel plant experiment in which potted black mustard (Brassica nigra L.) plants were placed out in a subset of these sites (n = 10) and either bagged to exclude pollinators or left open for pollinator access. Then, we measured fruit and seed set of sentinel plants to compare pollination function among the restoration and land-use history treatments. Seed set and fruit set of sentinel plants were higher in open than bagged plants, indicating that this model system effectively measured pollination, but we found no differences in pollination based on restoration or agricultural history. These results indicate that although pollinator communities may show clear responses to restoration that are largely independent of prior land-use impacts, this does not necessarily translate into differences in pollination function after restoration.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1926

Water Model Tests for Semirigid Airships

The design of complicated structures often presents problems of extreme difficulty which are frequently insoluble. In many cases, however, the solution can be obtained by tests on suitable models. These model tests are becoming so important a part of the design of new engineering structures that their theory has become a necessary part of an engineer's knowledge. For balloons and airships water models are used. These are models about 1/30 the size of the airship hung upside down and filled with water under pressure. The theory shows that the stresses in such a model are the same as in the actual airship. In the design of the Army Semirigid Airship RS-1 no satisfactory way was found to calculate the stresses in the keel due to the changing shape of the bag. For this purpose a water model with a flexible keel was built and tested. This report gives the theory of the design, construction, and testing of such a water model.

Tuckerman, L.B.↗

DOE OSTI2014

In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the constructed (c) DTB and (d) DTF regression models to predict the T. pyriformis toxicity of diverse chemicals. - Highlights: • Ensemble learning (EL) based models constructed for toxicity prediction of chemicals • Predictive models used a few simple non-quantum mechanical molecular descriptors. • EL-based DTB/DTF models successfully discriminated toxic and non-toxic chemicals. • DTB/DTF regression models precisely predicted toxicity of chemicals in multi-species. • Proposed EL based models can be used as tool to predict toxicity of new chemicals.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

Recent thermodynamic results from lattice QCD analyzed within a quasiparticle model

The thermodynamic behavior of QCD matter at high temperature is currently studied by lattice QCD theory. The main features are the fast rise of the energy density {epsilon} around the critical temperature T{sub c} and the large trace anomaly of the energy momentum tensor <{Theta}{sub {mu}}{sup {mu}}>={epsilon}-3P, which hints at a strongly interacting system. Such features can be accounted for by employing a massive quasiparticle model with a temperature-dependent bag constant. Recent lattice QCD calculations with physical quark masses by the Wuppertal-Budapest group show a slower increase of {epsilon} and a smaller <{Theta}{sub {mu}}{sup {mu}}> peak with respect to previous results from the HotQCD Collaboration. We investigate the implications of such differences from the point of view of a quasiparticle model, also discussing light and strange quark number susceptibilities. Furthermore, we predict the impact of these discrepancies on the temperature dependence of the transport properties of matter, like the shear and bulk viscosities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗

DOE OSTI2014

Bag breakup of low viscosity drops in the presence of a continuous air jet

This work examines the breakup of a single drop of various low viscosity fluids as it deforms in the presence of continuous horizontal air jet. Such a fragmentation typically occurs after the bulk liquid has disintegrated upon exiting the atomizer and is in the form of an ensemble of drops which undergo further breakup. The drop deformation and its eventual disintegration is important in evaluating the efficacy of a particular industrial process, be it combustion in automobile engines or pesticide spraying in agricultural applications. The interplay between competing influences of surface tension and aerodynamic disruptive forces is represented by the Weber number, We, and Ohnesorge number, Oh, and used to describe the breakup morphology. The breakup pattern considered in our study corresponds to that of a bag attached to a toroidal ring which occurs from ∼12 < We < ∼16. We aim to address several issues connected with this breakup process and their dependence on We and Oh which have been hitherto unexplored. The We boundary at which breakup begins is theoretically determined and the expression obtained, We=12(1+2/3Oh{sup 2}), is found to match well with experimental data ([L.-P. Hsiang and G. M. Faeth, Int. J. Multiphase Flow 21(4), 545–560 (1995)] and [R. S. Brodkey, “Formation of drops and bubbles,” in The Phenomena of Fluid Motions (Addison-Wesley, Reading, 1967)]). An exponential growth in the radial extent of the deformed drop and the streamline dimension of the bag is predicted by a theoretical model and confirmed by experimental findings. These quantities are observed to strongly depend on We. However, their dependence on Oh is weak.

42 ENGINEERING↗

NASA NTRS2020

Fisher's Peak Ecological Forecasting - Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation

Lauren Lad↗

NASA NTRS2020

Fisher's Peak Ecological Forecasting: Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation.

DEVELOP Tech Paper↗

NASA NTRS2018

Impacts of Snow and Cloud Covers on Satellite-Derived PM 2.5 Levels

Satellite aerosol optical depth (AOD) has been widely employed to evaluate ground fine particle (PM 2.5 ) levels, whereas snow/cloud covers often lead to a large proportion of non-random missing AOD. As a result, the fully covered and unbiased PM 2.5 estimates will be hard to generate. Among the current approaches to deal with the data gap issue, few have considered the cloud-AOD relationship and none of them have considered the snow-AOD relationship. This study examined the impacts of snow and cloud covers on AOD and PM 2.5 and made full-coverage PM 2.5 predictions with the consideration of these impacts. To estimate the missing AOD, daily gap-filling models with snow/cloud fractions and meteorological covariates were developed using the random forest algorithm. By using these models in New York State, a daily AOD data set with a 1-km resolution was generated with a complete coverage. The“out-of-bag” R 2 of the gap-filling models averaged 0.93 with an interquartile range from 0.90 to 0.95. Subsequently, a random forest-based PM 2.5 prediction model with the gap-filled AOD and covariates was built to predict fully covered PM 2.5 estimates. A ten-fold cross-validation for the prediction model showed a good performance with an R 2 of 0.82. In the gap-filling models, the snow fraction was of higher significance in the snow season compared with the rest of the year. The prediction models fitted with/without the snow fraction also suggested the discernible changes in PM 2.5 patterns, further confirming the significance of this parameter. Compared with the methods without considering snow and cloud covers, our PM 2.5 prediction surfaces showed more spatial details and reflected small-scale terrain-driven PM 2.5 patterns. The proposed methods can be generalized to the areas with extensive snow/cloud covers and large proportions of missing satellite AOD for predicting PM 2.5 levels with high resolutions and complete coverage.

AOD↗

DOE OSTI2018

Preprocessing Prediction of Advanced Algorithms for Medical Imaging

Advanced medical imaging algorithms (such as bone removal, vessel segmentation, or a lung nodule detection) can provide extremely valuable information to the radiologists, but they might sometimes be very time consuming. Being able to run the algorithms in advance can be a possible solution. However, we do not know which algorithm to run on a given dataset before it is actually used. It is possible to manually insert matching rules for preprocessing algorithms, but it requires high maintenance and does not work well in practice. This paper presents a dynamic machine learning solution for predicting which advanced visualization (AV) algorithm needs to be applied on a given series. The system gets a handful of free text DICOM tags as an input and builds a model in the clinical setting. It incorporates a Bag of Words (BOW) feature extractor and a Random Forest classifier. The approach was tested on two datasets from clinical sites which use different languages and varying scanner models. We show that even without feature extraction, sensitivity of above 90% can be reached on both of them. By using BOW feature extractor, precision and sensitivity can usually be further improved. Even on a noisy and highly unbalanced dataset, only around 100 samples were needed to reach sensitivity of above 80% and specificity of above 97%. We show how the solution can be part of a Smart Preprocessing mechanism in a viewing software. Using such a system will ultimately minimize the time to launch studies and improve radiologists reading time efficiency.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRSDate not supplied

Updated Analysis of the Trash Compaction and Processing System: Water Collected from Trash, Evaluation of the Source Contaminant Control System, and Zotek® F30 Foam Processing

The Trash Compaction and Processing System (TCPS) aims to reduce volume, biologically safen, physically stabilize, manage effluents, and recover resources from astronaut trash in the International Space Station (ISS). At NASA Ames Research Center (ARC), there are two test systems: the Heat Melt Compactor (HMC), which compacts the trash into a tile with temperature and pressure, and the Source Contaminant Control System (SCCS), which is the gas management subsystem aimed to reduce contaminants by converting them into carbon dioxide (CO 2 ) and water (H 2 O) vapor. Both the HMC and SCCS serve as test systems that support TCPS development by conducting risk reduction activities associated with an ISS technology demonstration. In this paper, the risk reduction activities discussed are the testing of different trash models for operational scenarios in the HMC, investigating the water extracted from those trash models, and managing the gaseous effluents from the trash via contaminant conversion through the SCCS. The HMC has undergone several tests of different trash models and cases in which a containment bag is used or not. For the first topic, this paper will analyze the water collected and recovered from these tests and analyze the effect of specific trash containment bags. For the second topic, this paper will individually evaluate the carbon bed and catalytic oxidizer (CatOx) to understand what components the carbon bed removes and what contaminants are converted in the CatOx. For the third and final topic, this paper will discuss Zotek® F30 foam processing in the HMC unit and testing verification in correlation to defined TCPS requirements. A foam model was added to reduce the volume of foam that take up space in the ISS. Overall, this paper is a compilation and an updated analysis of tests conducted in the lab-scale TCPS at ARC within the past year.

TCPS↗