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NextSTEP Appendix A Modular ECLSS Effort Lessons Learned

NASA’s Artemis program provides the first steps for earth-independent exploration starting with crewed habitats in cislunar space and progressing toward crewed landings on the lunar surface that will prepare systems and crews for the exploration of Mars. The Next Space Technology for Exploration Partnerships (NextSTEP) is a public-private partnership model that facilitates commercial development of deep space exploration capabilities in support of more extensive human spaceflight missions in and beyond cislunar space. NASA issued the original NextSTEP Broad Agency Announcement (BAA) to U.S. industry in late 2014 and issued the second BAA (NextSTEP-2) in April 2016. The first appendix under NextSTEP-2, Appendix A, focused on developing deep space habitation concepts, engineering design and development, and risk reduction efforts leading to a habitation capability in cislunar space. NASA solicited concepts to develop and refine the evolvable, modular architecture, functional allocation options, standards, and common interfaces required to enable interoperability of the aggregate system to provide long duration deep space transit habitation, specifically enhancements and testing of deep space Environmental Control and Life Support Systems (ECLSS). Collins Aerospace, formerly UTC Aerospace Systems (UTAS), was awarded a Phase 1 and subsequent Phase 2 contract to “develop concepts that group ECLS systems into logical modules maximizing the use of common components and the development of unique methods and design concepts that support in-flight maintenance and repair for future exploration systems.” This paper summarizes the work accomplished under this effort, the lessons that can be applied to development of forthcoming habitation elements, and the gaps remaining to achieve a more resilient, maintainable, repairable and adaptable system capable of installation on a wide variety of habitat platforms. A primary accomplishment of this effort is the development and maturation of a modular palletization concept to enable standard rack interfaces, post-launch outfitting, and decoupling of structural supports that withstand launch environments from those needed for lower on-orbit loads in order to reduce installed mass and repurposing of panels within the habitat. In the course of the effort, Collins assessed numerous architecture trades, including the use of condensing and noncondensing heat exchangers, the ability of modular units to accommodate various habitat volumes and thermal loading, and the most appropriate order of and timing of delivery of regenerative ECLSS hardware to orbital habitats. In addition to the modularity of hardware elements, Collins developed software approaches for distributed/modular command, control, and communication systems and innovative Bayesian fault detection and isolation techniques. Finally, the effort explored advanced maintainability and supportability concepts including the definition of maintenance units (MUs) in place of the traditional Orbital Replacement Units (ORUs), increasing parts commonality to reduce the number and type of spare parts, the use of augmented reality to guide crews during maintenance and repair procedures, and how crews would prepare for and recover from long durations of habitat dormancy. Now that the NextSTEP Modular ECLSS effort has come to a close, it’s important to identify the lessons learned and where they can be leveraged to improve NASA’s broader program of ECLSS technology development and demonstration and ultimately how they can increase the performance of future surface and orbital habitats.

NextSTEP↗

NextSTEP Appendix A Modular ECLSS Effort Lessons Learned

NASA’s Artemis program provides the first steps for earth-independent exploration starting with crewed habitats in cislunar space and progressing toward crewed landings on the lunar surface that will prepare systems and crews for the exploration of Mars. The Next Space Technology for Exploration Partnerships (NextSTEP) is a public-private partnership model that facilitates commercial development of deep space exploration capabilities in support of more extensive human spaceflight missions in and beyond cislunar space. NASA issued the original NextSTEP Broad Agency Announcement (BAA) to U.S. industry in late 2014 and issued the second BAA (NextSTEP-2) in April 2016. The first appendix under NextSTEP-2, Appendix A, focused on developing deep space habitation concepts, engineering design and development, and risk reduction efforts leading to a habitation capability in cislunar space. NASA solicited concepts to develop and refine the evolvable, modular architecture, functional allocation options, standards, and common interfaces required to enable interoperability of the aggregate system to provide long duration deep space transit habitation, specifically enhancements and testing of deep space Environmental Control and Life Support Systems (ECLSS). Collins Aerospace, formerly UTC Aerospace Systems (UTAS), was awarded a Phase 1 and subsequent Phase 2 contract to “develop concepts that group ECLS systems into logical modules maximizing the use of common components and the development of unique methods and design concepts that support in-flight maintenance and repair for future exploration systems.” This paper summarizes the work accomplished under this effort, the lessons that can be applied to development of forthcoming habitation elements, and the gaps remaining to achieve a more resilient, maintainable, repairable and adaptable system capable of installation on a wide variety of habitat platforms. A primary accomplishment of this effort is the development and maturation of a modular palletization concept to enable standard rack interfaces, post-launch outfitting, and decoupling of structural supports that withstand launch environments from those needed for lower on-orbit loads in order to reduce installed mass and repurposing of panels within the habitat. In the course of the effort, Collins assessed numerous architecture trades, including the use of condensing and noncondensing heat exchangers, the ability of modular units to accommodate various habitat volumes and thermal loading, and the most appropriate order of and timing of delivery of regenerative ECLSS hardware to orbital habitats. In addition to the modularity of hardware elements, Collins developed software approaches for distributed/modular command, control, and communication systems and innovative Bayesian fault detection and isolation techniques. Finally, the effort explored advanced maintainability and supportability concepts including the definition of maintenance units (MUs) in place of the traditional Orbital Replacement Units (ORUs), increasing parts commonality to reduce the number and type of spare parts, the use of augmented reality to guide crews during maintenance and repair procedures, and how crews would prepare for and recover from long durations of habitat dormancy. Now that the NextSTEP Modular ECLSS effort has come to a close, it’s important to identify the lessons learned and where they can be leveraged to improve NASA’s broader program of ECLSS technology development and demonstration and ultimately how they can increase the performance of future surface and orbital habitats.

NextSTEP↗

Electro optical system to measure strains at high temperature

The goals of this proposal were to develop a prototype of an electro-optics system for the measurement of strains in structures at high temperatures and to perform a test under field conditions. In the research task section, the topics addressed include: (1) correction of the effect of vibrations and thermal currents by means of an active compensation system; (2) reduction of the speckle noise by means of electronic filter and TV signal reconstruction circuit; (4) compensation of the rigid body motions by mounting the camera in a universal motion system; and (5) removal of phase errors left by the active compensation system by dynamic reading. In the design and construction section, the topics addressed include: (1) preliminary design; (2) final design; (3) software development; (4) signal conditioning; (5) data processing; (6) recorrelation of two holograms in the presence of rigid body motions; and (7) phase extraction using a computer generated image. Testing in the high temperature oven is also addressed.

Sciammarella, Cesar A.↗

Predicting Ice Sheet and Climate Evolution at Extreme Scales

A main research objectives of PISCEES is the development of formal methods for quantifying uncertainties in ice sheet modeling. Uncertainties in simulating and projecting mass loss from the polar ice sheets arise primarily from initial conditions, surface and basal boundary conditions, and model parameters. In general terms, two main chains of uncertainty propagation may be identified: 1. inverse propagation of observation and/or prior onto posterior control variable uncertainties; 2. forward propagation of prior or posterior control variable uncertainties onto those of target output quantities of interest (e.g., climate indices or ice sheet mass loss). A related goal is the development of computationally efficient methods for producing initial conditions for an ice sheet that are close to available present-day observations and essentially free of artificial model drift, which is required in order to be useful for model projections (“initialization problem”). To be of maximum value, such optimal initial states should be accompanied by “useful” uncertainty estimates that account for the different sources of uncerainties, as well as the degree to which the optimum state is constrained by available observations. The PISCEES proposal outlined two approaches for quantifying uncertainties. The first targets the full exploration of the uncertainty in model projections with sampling-based methods and a workflow managed by DAKOTA (the main delivery vehicle for software developed under QUEST). This is feasible for low-dimensional problems, e.g., those with a handful of global parameters to be inferred. This approach can benefit from derivative/adjoint information, but it is not necessary, which is why it often referred to as “non-intrusive”. The second approach makes heavy use of derivative information from model adjoints to address quantifying uncertainty in high-dimensions (e.g., basal boundary conditions in ice sheet models). The use of local gradient, or Hessian information (i.e., second derivatives of the cost function), requires additional code development and implementation, and is thus often referred to as an “intrusive” approach. Within PISCEES, MIT has been tasked to develop methods for derivative-based UQ, the ”intrusive” approach discussed above. These methods rely on the availability of first (adjoint) and second (Hessian) derivative code, developed through intrusive methods such as algorithmic differentiation (AD). While representing a significant burden in terms of code development, derivative-baesd UQ is able to cope with very high-dimensional uncertainty spaces. That is, unlike sampling methods (all variations of Monte Carlo), calculational burden is independent of the dimension of the uncertainty space. This is a significant advantage for spatially distributed uncertainty fields, such as threedimensional initial conditions, three-dimensional parameter fields, or two-dimensional surface and basal boundary conditions. Importantly, uncertainty fields for ice sheet models generally fall into this category.

97 MATHEMATICS AND COMPUTING↗

Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute

At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes are best suited for the types of models we see in neuroscience. In 2015, a Frontiers Research Topic “Python in neuroscience” by Muller et al. triggered and documented a revolution in the neuroscience community, namely in the usage of the scripting language Python as a common language for interfacing with simulation codes and connecting between applications. The review by Einevoll et al. documented that simulation tools have since further matured and become reliable research instruments used by many scientific groups for their respective questions. Open source and community standard simulators today allow research groups to focus on their scientific questions and leave the details of the computational work to the community of simulator developers. A parallel development has occurred, which has been barely visible in neuroscientific circles beyond the community of simulator developers: Supercomputers used for large and complex scientific calculations have increased their performance from ~10 TeraFLOPS (10 13 floating point operations per second) in the early 2000s to above 1 ExaFLOPS (10 18 floating point operations per second) in the year 2022. This represents a 100,000-fold increase in our computational capabilities, or almost 17 doublings of computational capability in 22 years. Moore's law (the observation that it is economically viable to double the number of transistors in an integrated circuit every other 18–24 months) explains a part of this; our ability and willingness to build and operate physically larger computers, explains another part. It should be clear, however, that such a technological advancement requires software adaptations and under the hood, simulators had to reinvent themselves and change substantially to embrace this technological opportunity. It actually is quite remarkable that—apart from the change in semantics for the parallelization—this has mostly happened without the users knowing. The current Research Topic was motivated by the wish to assemble an update on the state of neuroscientific software (mostly simulators) in 2022, to assess whether we can see more clearly which scientific questions can (or cannot) be asked due to our increased capability of simulation, and also to anticipate whether and for how long we can expect this increase of computational capabilities to continue.

biophysically detailed models↗

Boundary-Layer Flow Simulations Over Ablating Woven Thermal Protection System Material

Spallation is the mechanical removal of small chunks of material gets removed typically due to high shear conditions of the flow field. This reduces the ability of the thermal protection system (TPS) material to protect the spacecraft as well as cause turbulence in the flow causing higher heating rates. In this work, we focus on the material removal through ablation and high shear flow within the boundary layer region of woven TPS material. Woven TPS (WTPS) material is the latest class of material developed by NASA, to be used within the next generation of space flights. They are complex interlocked weaves designed to create a rigid structure that is highly resistant to heat and can be easily designed and tailored for a wide variety of entry environments. Due to material removal resulting from chemical degradation, the structural integrity of TPS material is affected. Spallation occurs when this structurally compromised material is exposed to the high shear flow conditions within the boundary layer. In order to understand the spallation mechanism within WTPS material, we first perform the material removal simulations which occur primarily through oxidation to obtain the microstructure at various stages of degradation. These simulations are performed using the Porous Microstructure Analysis (PuMA) software developed at NASA Ames. The micro-structure geometry used within these simulations were generated artificially to be similar to the 3D weave architecture of MSR-EEV (Mars Sample Return - Earth Entry Vehicle). The various eroded TPS micro-structures are then subjected to the boundary layer flow conditions to obtain critical surface quantities which contribute to the structural failure mechanism such as heat flux, pressure, and shear stress. The direct simulation Monte Carlo (DSMC) methodology is used to perform these simulations in order to accurately capture the strong gradients within the high-temperature boundary layer flow over the intricate geometry of WTPS material. The boundary layer profile is directly taken from the Computational Fluid Dynamics (CFD) simulation and provided as boundary conditions to the DSMC inlet and outlet. Further, the variation of these properties as the microstructure undergoes changes due to oxidation is also investigated. Finally, these quantities are used as input in PuMA to understand the material expansion/compression and strain within the woven TPS geometry and help in developing a comprehensive spallation and structure failure model.

microstructure↗

Boundary-Layer Flow Simulations Over Ablating Woven Thermal Protection System Material

Spallation is the mechanical removal of small chunks of material gets removed typically due to high shear conditions of the flow field. This reduces the ability of the thermal protection system (TPS) material to protect the spacecraft as well as cause turbulence in the flow causing higher heating rates. In this work, we focus on the material removal through ablation and high shear flow within the boundary layer region of woven TPS material. Woven TPS (WTPS) material is the latest class of material developed by NASA, to be used within the next generation of space flights. They are complex interlocked weaves designed to create a rigid structure that is highly resistant to heat and can be easily designed and tailored for a wide variety of entry environments. Due to material removal resulting from chemical degradation, the structural integrity of TPS material is affected. Spallation occurs when this structurally compromised material is exposed to the high shear flow conditions within the boundary layer. In order to understand the spallation mechanism within WTPS material, we first perform the material removal simulations which occur primarily through oxidation to obtain the microstructure at various stages of degradation. These simulations are performed using the Porous Microstructure Analysis (PuMA) software developed at NASA Ames. The micro-structure geometry used within these simulations were generated artificially to be similar to the 3D weave architecture of MSR-EEV (Mars Sample Return - Earth Entry Vehicle). The various eroded TPS micro-structures are then subjected to the boundary layer flow conditions to obtain critical surface quantities which contribute to the structural failure mechanism such as heat flux, pressure, and shear stress. The direct simulation Monte Carlo (DSMC) methodology is used to perform these simulations in order to accurately capture the strong gradients within the high-temperature boundary layer flow over the intricate geometry of WTPS material. The boundary layer profile is directly taken from the Computational Fluid Dynamics (CFD) simulation and provided as boundary conditions to the DSMC inlet and outlet. Further, the variation of these properties as the microstructure undergoes changes due to oxidation is also investigated. Finally, these quantities are used as input in PuMA to understand the material expansion/compression and strain within the woven TPS geometry and help in developing a comprehensive spallation and structure failure model.

microstructure↗

Relative Navigation of Formation Flying Satellites

The Guidance, Navigation, and Control Center (GNCC) at Goddard Space Flight Center (GSFC) has successfully developed high-accuracy autonomous satellite navigation systems using the National Aeronautics and Space Administration's (NASA's) space and ground communications systems and the Global Positioning System (GPS). In addition, an autonomous navigation system that uses celestial object sensor measurements is currently under development and has been successfully tested using real Sun and Earth horizon measurements.The GNCC has developed advanced spacecraft systems that provide autonomous navigation and control of formation flyers in near-Earth, high-Earth, and libration point orbits. To support this effort, the GNCC is assessing the relative navigation accuracy achievable for proposed formations using GPS, intersatellite crosslink, ground-to-satellite Doppler, and celestial object sensor measurements. This paper evaluates the performance of these relative navigation approaches for three proposed missions with two or more vehicles maintaining relatively tight formations. High-fidelity simulations were performed to quantify the absolute and relative navigation accuracy as a function of navigation algorithm and measurement type. Realistically-simulated measurements were processed using the extended Kalman filter implemented in the GPS Enhanced Inboard Navigation System (GEONS) flight software developed by GSFC GNCC. Solutions obtained by simultaneously estimating all satellites in the formation were compared with the results obtained using a simpler approach based on differencing independently estimated state vectors.

Long, Anne↗

Novel Image Processing Interface to Relate DSB Spatial Distribution from Immunofluorescence Foci Experiments to the State-of-the-Art Models of DNA Breakage

A recently developed software (NASARadiationTrackImage) allows a quick and automatic segmentation of foci that indicate spatial localization of specific proteins that are visualized by immunofluorescence. Of interest are the spatial and temporal distribution of foci such as gammaH2AX, a signal of the phosphorylation of a variant of the histone H2A that has been shown to correspond to DSBs, or proteins involved in DSB processing, such as ATM, Rad51, and p53, following exposures of human cells to high charge and energy (HZE) ion irradiation. Experimental data are recorded as sets of two-dimensional images in color with cells and foci of gammaH2AX, ATM, Rad51 or others shown. Different cells, levels of radiation and timing after radiation were recorded. The software allows us to calculate the number of foci per cell, overall intensity of light in foci and their spatial organization. A simple statistical model allows for testing of foci overlap (eclipse). A more complex statistical model previously known as DNAbreak simulates track structure and random chromosome geometry. It has one adjustable parameter corresponding to an average intensity of DSB creation in cubic micrometers of DNA volume per particle track or unit dose. Its limitation is the low-resolution limit both in physical space and DSB's along DNA. It works adequately on the scale of a cell and provides further insights on how the geometry of tracks and DNA affects genomic damage of the cell and subsequent repair. Future developments of the model for the description of the time evolution of DNA damage response proteins, and more robust track structure models will be discussed.

Ponomarev, A. L.↗

Techno-Economic Analysis of a Microgrid System for Rural Communities in the United States

Access to running water has been a pressing issue in many developing countries across the globe, and also continues to be a problem in some rural areas in the United States. Today, more than two million Americans living in rural areas lack access to basic water supply and infrastructure. Rural communities tend to be located in environmentally fragile areas with poor economic conditions, making access to appropriate, low-cost technology for clean water supply and sanitation more challenging. In addition, many of the water resources located in these areas are being jeopardized by climate change in recent years. This research proposes a photovoltaic (PV)-battery microgrid system for powering water pumps in off-grid areas in an effort to identify economically and technologically feasible solution to the problems. Utilizing the HOMER Pro software, developed by the U.S. National Renewable Energy Laboratory (NREL), the case of the Navajo Nation is examined by analyzing the effects of this region's air temperature on the life and performance of battery storage and the economics of the proposed microgrid system.

battery↗

BOSC 2019, the 20th annual Bioinformatics Open Source Conference

The Bioinformatics Open Source Conference is a volunteer-organized meeting that covers open source software development and open science in bioinformatics. Launched in 2000, BOSC has been held every year since. BOSC 2019, the 20th annual BOSC, took place as one of the Communities of Special Interest (COSIs) at the Intelligent Systems for Molecular Biology meeting (ISMB/ECCB 2019). The two-day meeting included a total of 46 talks and 55 posters, as well as eight Birds of a Feather interest groups. The keynote speaker was University of Cape Town professor Dr. Nicola Mulder, who spoke on “Building infrastructure for responsible open science in Africa”. Immediately after BOSC 2019, about 50 people participated in the two-day CollaborationFest (CoFest for short), an open and free community-driven event at which participants work together to contribute to bioinformatics software, documentation, training materials, and use cases.

97 MATHEMATICS AND COMPUTING↗

New Dielectric Measurement Data to Determine the Permittivity of Seawater at 1.4313 Hz

This paper describes the new measurements - made in 2010-2011 - of the dielectric constant of seawater at 1.413 GHz using a resonant cavity technique. The purpose of these measurements is to develop an accurate relationship concerning the dependence of the dielectric constant of seawater on temperature and salinity for use by the Aquarius inversion algorithm. Aquarius is a NASA/CONAE satellite mission launched in June of 2011 with the primary mission of measuring global sea surface salinity with a 1.413 GHz radiometer to an accuracy of 0.2 psu. A brass microwave cavity resonant at 1.413 GHz has been used to measure the dielectric constant of seawater. The seawater is introduced into the cavity through a capillary glass tube having an inner diameter of 0.1 mm. The change of resonant frequency and the cavity Q value are used to determine the real and imaginary parts of the dielectric constant of seawater. Measurements are automated with Visual Basic software developed at the George Washington University. In this paper, new results from measurements made since September 2010 will be presented for salinities of 30, 35 and 38 psu with a temperature range of 0 C to 35 C in intervals of 5 C. These measurements are more accurate than earlier measurements made in 2008. The new results will be compared to the Klein-Swift (KS) and Meissner-Wentz (MW) model functions. The importance of an accurate model function will be illustrated by using these model functions to invert the Aquarius brightness temperature to retrieve the salinity values. The salinity values will be compared to co-located in situ data collected by Argo buoys.

Lang, R.↗

Integrated Test Approach

This paper describes a testing methodology undertaken on the Facilities Development and Operations Contract (FDOC) by Lockheed Martin. The methodology was defined with the intent of reducing project schedule time to enable NASA's Johnson Space Center (JSC) to be able to deliver the Mission Control Center (MCC) 21 project as quickly as possible. 21 represents the 21st century where NASA JSC is updating its control center with new technology and operational concepts in order to support NASA customers wanting to use control center assets to support space vehicle operations. In collaboration with the NASA customer, a new test concept was conceived early during MCC21 project planning with the goal of reducing project delivery time. One enabler that could help reduce delivery time was testing. Within the project, testing was performed by two entities, software development responsible for subsystem testing and system test responsible for system integration testing. The MCC21 project took a deliberate review of testing to determine how it could be performed differently to realize an overall reduction in test time to support the goal of a more rapid project delivery.

Cotton, Will↗

Developing A Fully Implicit Compressible Flow Valve Model in RELAP-7 and Its Application in Short Term BWR Station Black-Out Analyses

This paper presents a set of dynamical models for SRV simulation and their implementation in the RELAP-7 code, which is a new reactor system analysis code being developed at INL. RELAP-7 is based on the MOOSE (the Multi-Physics Object-Oriented Simulation Environment) framework. The compressible flow SRV model covers three different sets of models: fully closed case, subsonic case, and choking case. The RELAP-7 is a fully implicit code and the preconditioned Jacobian-free Newton-Krylov (JFNK) method is used to solve the discretized nonlinear problem. The JFNK method generally needs a good preconditioning scheme to be effective and efficient. There are different ways to precondition the JFNK method. In RELAP-7, two main options are used to obtain the preconditioning matrix: (1) FDP (Finite Difference Preconditioning) option which uses the default finite differencing method provided in the PETSc package. PETSc is the numerical solver software developed by Argonne National Laboratory and used by MOOSE as the numerical solution engine; (2) SMP (Single Matrix Preconditioning) option which requires code developers to provide approximate analytical Jacobian inputs for the important diagonal and off-diagonal terms. Due to the strong discontinuity in the residual vector space when the compressible flow valve model switches from one set of model to another, FDP option cannot guarantee convergence. Instead, accurate analytical Jacobain terms are provided for the compressible flow valve model. With the SMP option selected, the compressible flow valve model can be solved efficiently under different cases. The developed compressible flow valve model has been used for SRV component simulation in several simplified BWR SBO (Station Black-Out) simulations with RELAP-7. This paper only presents cases for short-term SBO in which all the safety systems fail to start and function properly when SBO occurs. Consequently, only the SRVs automatically open and close periodically to control the primary system pressure and discharge the high temperature and high pressure steam into the suppression pool. Although simplified, this case is quite similar to what happened in Fukushima Daiichi Unit 1. Unit 1 had no RCIC system, while the isolation condenser system was believed to be non-functioning, or only available for a very short period of time during the accident. Therefore, the Unit 1 reactor core reached a fuel failure temperature only a few hours into the accident. Two short-term SBO cases will be compared: one with single SRV discharge line which represents all the SRV lines and another case with multi-group SRVs which represent each group of SRV line with different setting points.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sorption Modeling and Verification for Off-Gas Treatment

This project was successfully executed to provide valuable adsorption data and improve a comprehensive model developed in previous work by the authors. Data obtained were used in an integrated computer program to predict the behavior of adsorption columns. The model is supported by experimental data and has been shown to predict capture of off gas similar to that evolving during the reprocessing of nuclear waste. The computer program structure contains (a) equilibrium models of off-gases with the adsorbate; (b) mass-transfer models to describe off-gas mass transfer to a particle, diffusion through the pores of the particle, and adsorption on the active sites of the particle; and (c) incorporation of these models into fixed bed adsorption modeling, which includes advection through the bed. These models are being connected with the MOOSE (Multiphysics Object-Oriented Simulation Environment) software developed at the Idaho National Laboratory through DGOSPREY (Discontinuous Galerkin Off-gas SeParation and REcoverY) computer codes developed in this project. Experiments for iodine and water adsorption have been conducted on reduced silver mordenite (Ag0Z) for single layered particles. Adsorption apparatuses have been constructed to execute these experiments over a useful range of conditions for temperatures ranging from ambient to 250°C and water dew points ranging from -69 to 19°C. Experimental results were analyzed to determine mass transfer and diffusion of these gases into the particles and to determine which models best describe the single and binary component mass transfer and diffusion processes. The experimental results were also used to demonstrate the capabilities of the comprehensive models developed to predict single-particle adsorption and transients of the adsorption-desorption processes in fixed beds. Models for adsorption and mass transfer have been developed to mathematically describe adsorption kinetics and transport via diffusion and advection processes. These models were built on a numerical framework for solving conservation law problems in one-dimensional geometries such as spheres, cylinders, and lines. Coupled with the framework are specific models for adsorption in commercial adsorbents, such as zeolites and mordenites. Utilizing this modeling approach, the authors were able to accurately describe and predict adsorption kinetic data obtained from experiments at a variety of different temperatures and gas phase concentrations. A demonstration of how these models, and framework, can be used to simulate adsorption in fixed- bed columns is provided. The CO 2 absorption work involved modeling with supportive experimental information. A dynamic model was developed to simulate CO 2 absorption using high alkaline content water solutions. The model is based upon transient mass and energy balances for chemical species commonly present in CO 2 absorption. A computer code was developed to implement CO 2 absorption with a chemical reaction model. Experiments were conducted in a laboratory scale column to determine the model parameters. The influence of geometric parameters and operating variables on CO 2 absorption was studied over a wide range of conditions. Continuing work could employ the model to control column operation and predict the absorption behavior under various input conditions and other prescribed experimental perturbations. The value of the validated models and numerical frameworks developed in this project is that they can be used to predict the sorption behavior of off-gas evolved during the reprocessing of nuclear waste and thus reduce the cost of the experiments. They can also be used to design sorption processes based on concentration limits and flow-rates determined at the plant level.

42 ENGINEERING↗

Bringing wings of change - NASA's airfoil research program

A review is presented of progress in attaining technical objectives in three areas of semiautomatic airfoil development: software, hardware, and applications. Software objectives seek improved mathematical models and computer codes for flow analysis and design optimization for a variety of conditions. The 17-step iterative computer model used in designing the GA (W)-1 airfoil is effective but not yet fully automated; with present methods only single-point computer optimization is possible. Hardware objectives calling for improvement in test facilities and techniques are met in part by the introduction of the Langley (F-3C) wind tunnel for independent evaluation of transonic Mach number and Reynolds effects up to 12-16 million, and by a two-dimensional test section for the Langley 1/3 transonic cryogenic tunnel which will extend the Reynolds number to 50 million. The current status of low-speed, thin, and rotorcraft airfoil development programs is discussed.

Pierpont, P. K.↗

Development of Automated Pipeline for Time-Resolved Link-Wise Vehicular Energy Consumption in the Chattanooga, TN Road Network

The Department of Energy (DOE) has shown strong interest in detecting energy inefficiencies in regional road networks, so as to derive energy consumed at a high spatial temporal resolution. We have developed a workflow to automate the estimation of time-resolved vehicular energy consumption over each link in a road network of interest. The road network used in the current work is centered around the city of Chattanooga, Tennessee and its bordering regions. Utilizing the most mature road network for the Chattanooga, TN region, vehicle speed & count data from TomTom in conjunction with machine learning methods, we have developed an automated pipeline to estimate energy consumption for every link in the network. The first step in the pipeline is ingesting vehicle probe counts and speed estimates from TomTom API. In the next step, the probe counts, speed profiles and other exogenous data (i.e. road types, weather data, ground-truth volume counts and more) were used as input to a supervised learning algorithm to estimate the number of vehicles throughout the entire region for each road segment. These volume estimates were then mapped to a unified road network that contained additional important information such as percentage change in gradient across a link, number of lanes and link lengths that are features in pre-trained single vehicle energy-consumption models available with the RouteE software developed at NREL. The per vehicle energy consumption on each road link predicted using appropriate RouteE vehicular models were multiplied by the volume estimate for the corresponding link over a given time period to predict energy consumed per link for the time interval of interest. Currently, work is underway to improve both the RouteE per vehicle energy estimate and the volume estimates derived from TomTom probe counts. We have also explored the correlation of the link-wise energy estimates with the features of the pre-trained RouteE machine learning model in order to gain insight into what factors contribute most to the link-wise energy consumption.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

Floorspace.js

Floorspace.js is a 2D geometry editor. Users can define an explicit floor plan for each story of a building. A story-by-story interface makes it easy to develop space geometry and assign properties. Referencing satellite imagery or floor plan images, when available, speeds up geometry entry. Conversion of 2D to 3D geometry is currently out of scope for Floorspace.js, a reference implementation is available in the OpenStudio® SDK. Explicit floor plans allow more building-specific information than parameterized shoe-boxes but less information than a full 3D BIM model. Sloped walls, complex roofs, detailed shading structures, and other complex 3D structures are out of FloorspaceJS's scope. In general, if users have a 3D BIM model in a tool that can export a useful BEM representation then it is better to use that export than to recreate a new model using FloorspaceJS. Re-usability and minimal dependencies were key design considerations for software developers. Web technologies can be used in both online and desktop applications. The editor was written in pure JavaScript for maximum portability and re-usability. A custom JavaScript Object Notation (JSON) file format was developed to ease integration with other applications. Custom JSON schema design was a key part of FloorspaceJS development.

Noland, Katie↗