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180 records · Page 10

Enhancing Worker Safety During Off-Site Construction of Energy-Efficient, Low-Carbon Exterior Envelope

The construction industry is not doing enough to embrace off-site modular construction. It is a missed opportunity for optimized energy efficiency because prefabricated exterior wall envelopes are lower in cost and faster and easier to install. Factory off-site construction offers improved safety for construction workers because work is done in a controlled environment, but lack of intent, understanding, and data is also a missed opportunity for enhancing worker safety. This research looks specifically at the prefabricated wall exterior envelope in the context of safety. The research question is "off-site factories build with ease of energy efficiency and lowered carbon emissions, but is the process safer?" This research was funded by NREL Student Training in Applied Research (STAR) program, University Partnerships Program, and Wells Fargo Bank. Key finding is that modular and prefabricated construction are perceived to be safer, but the accident rates are much higher than in the general construction and manufacturing industries. Proposed solutions to decrease accidents in off-site prefabricated construction includes safety training for workers, provide movable kiosks with PPE at workstations, ensure tools are well-maintained and place safety posters in visible locations. Future work includes improving worker safety to increase worker productivity, perform pilot demonstration, work with factory designers for new modular layout for worker safety, i.e., easy access to PPE kiosks, and work closely with OSHA so that they take notice of this safety niche.

drywall↗

SMART SiC Power ICs: Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits (Final Technical Report)

This collaborative project was initiated with the goal of developing Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits (SMART SiC Power ICs). In pursuit of this objective, innovative designs and fabrication processes were implemented, enabling the development of large-scale (>1 cm²) SiC Complementary Metal-Oxide-Semiconductor (CMOS) integrated circuits and high-voltage (400–600 V) lateral power MOSFETs (HV-LDMOS) on 150 mm 4H-SiC substrates. The resulting SMART SiC Power ICs are tailored to support a wide range of applications requiring diverse voltage and power levels, including automotive systems, industrial equipment, electronic data processing, energy harvesting, and power conditioning. To achieve the proposed ‘SMART’ technology for SiC ICs, the team focused on 1) the Development of highly scalable CMOS (with high channel mobilities for n-type and p-type MOSFETs), LDMOS (~600V, 10A rated), and IC technologies, 2) Establishment of a manufacturable process baseline in a production-grade-, 150mm, SiC fabrication facility, and 3) Demonstration of SMART SiC ICs. The project initially comprised of fabricating 5 lots. In lot 1 monolithic integration using a single process was achieved. Here, we were able to successfully accomplish Integrated HV NMOSFET with LV CMOS on N-epi/N+ Substrate. The HV NMOS demonstrated a Breakdown Voltage (BV) more than 600V. Circuit demonstration of CMOS was also another achievement from this lot. In lot 2, priority was in place for isolation and integration. Here we addressed the isolation concerns and integrated the HV NMOS and LV CMOS using the N-epi/P-epi/N+ substrate. Similar to the lot 1, we were able to achieve a BV of 600 V for HV NMOS. Optimized gate oxide process with high channel mobilities, better gate oxide reliability, development of SPICE models, successful ohmic process development, novel wafer area saving design layouts, P+ isolation schemes with channeling implantations and high temperature operational circuits demonstrations are some of the key highlights from lot 1 and lot2. In lot 3, discrete device performances of HV NMOS with a BV ~700V and reliable LV CMOS performances were achieved. Also, novel architectural solutions were successfully implemented to suppress the electric field crowding at the gate oxide for reliable operations. In lot 4, half bridge power driver ICs with a conversion efficiency of (target 90% to 95%) in the 1-5MHz switching frequency range for output power between 25 W to 3 kW have been included in. However, due to the unfortunate events of sudden foundry shutdown (SiCamore Semi) the processing of lot 4 wafers came to a complete stop (January 2024). Arrangements have recently been made to shift the fabrication to another foundry, General Electric Aerospace. The fabrication process now on course (as of December 2024). Characterizations are delayed due to this unfortunate circumstance. The proposed trench architectural-based devices and ICs (lot 5) underwent modifications from the original project proposal. This change was necessitated by limitations in the availability of trench-based processes at commercial production-grade fabrication facilities in the US. Apart from above achievements, a Process Development Kit (PDK) was successfully developed for planar type SiC CMOS/LDMOS.

42 ENGINEERING↗

Applications of data mining technology to enhance O and M: automatic planning of electrical isolation with deep learning - 255

Data mining technology is now readily available, thanks to high powered, low cost computing resource and useful coding tools. We study several applications of data mining to enhance operation and maintenance (O and M), such as abnormality prediction, efficiency diagnosis, document traceability, image recognition, etc. In field support, we try automatic planning of electrical isolation with deep learning. Currently, a skilled engineer plans electrical isolation procedure with hundreds of the circuit diagrams and the related documents, taking man-hours. If this task becomes automatic, it is very efficient. The automatic planning has two issues. One is much calculation time of electrical circuit simulator, searching billions of electrical conducting paths. The other is interpretation of human fuzzy information, such as ease of work. Deep learning is helpful to resolve them. We performed a model case study of the electrical isolation. We applied a deep neural network (DNN) for dropping in the calculation time. We trained the circuit diagrams and the responses of the circuit simulator to the DNN, constructing an efficient path search algorithm in the DNN. The calculation time of the DNN was shorter by a factor of 32 for the model case, compared with that of the electrical circuit simulator. We applied a deep Q-network (DQN) for the interpretation of fuzzy information. The DQN optimized isolation procedure from the viewpoint of the work load with the equipment layout, related doses, and values of wet bulb globe temperature (WBGT) to prevent heatstroke. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning

Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. And, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.

97 MATHEMATICS AND COMPUTING↗

Multi-core and many-core shared-memory parallel raycasting volume rendering optimization and tuning

Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. In addition, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.

97 MATHEMATICS AND COMPUTING↗

An Evolutionary Computation System Design Concept for Developing Controlled Closed Ecosystems: An Intelligent Systems Approach to Foster Gravitational Ecosystem Research for Developing Sustainable Communities in Space and on Earth

An adjustably-autonomous intelligent systems approach for developing Closed Ecosystems (CESs) is presented, which includes a design concept and preliminary design details for the Controlled Closed-Ecosystem Development System (CCEDS) and the Orbiting Modular Artificial-Gravity Spacecraft (OMAGS). The paper is divided into three sections: CESs, the CCEDS Design Concept, and Orbiting Fractional-Gravity Closed Ecosystems OMAGS design concept. The first section briefly describes Closed EcoSystems (CESs), complex adaptive systems, biomes, microbial microbiomes, and their relevance for the study of astrobiology. This section also discusses initial efforts in the development of Closed Environment Life Support Systems (CELSSs) for sustainable communities in space and on Earth. This section concludes with a discussion of the bioregenerative life support system challenge of and the corresponding consequences due to the inverse relationship of the very small human biomass/non-human biomass ratio overall on the Earth with respect to the extremely large human biomass/non-human-biomass ratio found in cities and the International Space Station. The second section describes the CCEDS design concept, which consists of a population of controlled colonies of CES Modules (CESMs), each an integrated CES, continually generating data for an intelligent system that operates the CESs and their CESMs. A variety of CESM types and their use are briefly described. The CCEDS intelligent system uses an evolutionary computation algorithm described in this section to develop and optimize these CESs to increase their viability duration and the size of the animals they support with the ultimate goal to support populations of humans, both on Earth and in space. The CCEDS architecture, its five control subsystems, and its five evolutionary computation levels are also discussed. The section concludes with a discussion of several CCEDS design strategies. The third section summarizes the OMAGS design concept for a spacecraft with a payload consisting of CESs in an orbiting spacecraft centrifuge that operates for at least 5 years. The spacecraft concept is described including its 150cm-radius centrifuge with a 2 ton & 3,000 liter bioscience payload capacity for 24 CESMs. The centrifuge design has four physical levels for its CESMs, each level subject to a different fractional gravity level. This section presents the spacecraft benefits of being designed and operated such that the spacecraft and payload centrifuge wheel counter-rotate resulting in net zero angular momentum and zero gyroscopic forces. Artificial-gravity generation by centripetal acceleration is also discussed. This section concludes by showing the external specifications of the CESMs and their layout in the centrifuge, followed by discussing the multi-payload module rationale. In tandem, the CCEDS and OMAGS systems can be used to foster gravitational ecosystem research for developing sustainable communities in space and on Earth.

Dorais, Gregory A.↗

WavePropaGator : interactive framework for X-ray free-electron laser optics design and simulations

This article describes the WavePropaGator (WPG) package, a new interactive software framework for coherent and partially coherent X-ray wavefront propagation simulations. The package has been developed at European XFEL for users at the existing and emerging free-electron laser (FEL) facilities, as well as at the third-generation synchrotron sources and future diffraction-limited storage rings. The WPG addresses the needs of beamline scientists and user groups to facilitate the design, optimization and improvement of X-ray optics to meet their experimental requirements. The package uses the Synchrotron Radiation Workshop (SRW) C/C++ library and its Python binding for numerical wavefront propagation simulations. The framework runs reliably under Linux, Microsoft Windows 7 and Apple Mac OS X and is distributed under an open-source license. The available tools allow for varying source parameters and optics layouts and visualizing the results interactively. The wavefront history structure can be used for tracking changes in every particular wavefront during propagation. The batch propagation mode enables processing of multiple wavefronts in workflow mode. The paper presents a general description of the package and gives some recent application examples, including modeling of full X-ray FEL beamlines and start-to-end simulation of experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supercritical Reforming of Wet Ethanol for High Efficiency Direct-injection Heavy-duty Compression-ignition Engines

The purpose of the research was to investigate the potential of using a mature bio-fuel in heavy-duty compression ignition engines. By co-optimizing both the fuel characteristics and engine system the potential for a superior outcome was demonstrated. The use of wet bio-ethanol eliminates the majority of the energy intensive distilling and dehydrating fuel production processes, which moves the fuel towards carbon neutral and also lowers the fuel costs. The relatively high water content of the resulting fuel is leveraged in the proposed novel combustion system by incorporating an integrated high efficiency exhaust waste heat recovery system. This results in significantly higher thermal efficiency. In addition the combustion system features low criteria pollutant emissions and the potential to reduce the initial cost of the engine system hardware. Substantial societal benefits are demonstrated through the co-optimization of the fuel and engine system. A computational proof-of-concept study has been performed to demonstrate the potential benefits of a novel wet ethanol heavy-duty compression ignition combustion system featuring integrated exhaust waste heat recovery. A combined in-cylinder closed cycle 3D computational fluid dynamics (CFD) - 1D engine system simulation approach was used. The models were validated to baseline engine data using diesel fuel and then applied to the wet ethanol study. The original concept was to maximize exhaust waste heat recovery through supercritical reforming of the wet ethanol fuel. Phase I simulation results indicated that the optimal solution for maximum engine efficiency gains were realized through maximizing thermo-mechanical recuperation with negligible fuel reformation. The results show the potential to achieve impressive gains in brake thermal efficiency (BTE) over the base diesel engine. The potential to increase BTE up to 20.9% over the base diesel engine was demonstrated, with even larger gains possible through reduced in-cylinder heat transfer losses. The majority of the efficiency gains were realized through integrated high efficiency exhaust waste heat recovery. The concept also has the potential to achieve future ultra-low NO x emissions standards and negligible engine-out soot emissions. The mixing controlled combustion of high temperature wet ethanol features relatively low engine-out NO x emissions without the need for exhaust gas recirculation (EGR). The soot free combustion enabled by the relatively high oxygen content of ethanol also allows for the use of stoichiometric mixing controlled combustion, which is not practical with diesel fuel. When stoichiometric combustion is used a simple passive 3-way catalyst can be used for exhaust emissions after-treatment and near zero tailpipe emissions. The Phase I simulations results have defined the system layout and requirements in preparation for the Phase II experimental proof-of-concept study. The potential applications of the research include most current applications of diesel engines. The Phase I study focused on heavy-duty on-highway class 8 trucks. However, virtually any application that requires highly efficient clean power generation would benefit from the novel engine system proposed. The results indicate substantial fuel cost savings and reduced greenhouse gas emissions with similar or reduced initial system hardware costs compared to modern diesel engine systems.

09 BIOMASS FUELS↗

NSUF CoMET Project, Implementation Plan FY2019

The Combined Materials and Experiment Toolkit (CoMET) is an NSUF information management resource designed to give users access to the information and tools necessary for designing meaningful experiments and writing clear, structured proposals. NSUF has a milestone to deploy an experiment design expert system to the NSUF website to support applications for the FY2020 CINR, due on August 30, 2019. To meet this milestone, the CoMET project work for FY2019 focuses on three main objectives: 1.) Integrate the three NSUF web applications by linking data fields in one application with the data found in the others. The NSUF web applications are: The Rapid Turnaround Experiment (RTE) Proposal Solicitation system, the Nuclear Fuels and Materials Library (NFML) and the Nuclear Energy Infrastructure Database (NEID) and the researcher and technical staff account and profile management systems. 2.) Build an Experiment Design Wizard (expert system) that will guide users through the process of writing a statement of work for a CINR or RTE experiment. 3.) Build an Irradiation Effects Calculator to help a PI choose the best neutron irradiation facility for their needs, estimate the time needed to achieve their goals, and estimate the resulting radioactivity of their samples, post-irradiation. These objectives are designed to support the mission of the NSUF and optimize the experiment design portion of the proposal processes. The new researcher database will make finding collaborators easier. The wizard will provide the PI with early NSUF expertise so that their proposed experiments, at the “Letter of Intent” and “Pre-Application” stages are better designed to work within the available NSUF facilities. Utilization of these tools should reduce the proportion of proposals that are judged to be infeasible or “not ready” for NSUF access. It should also improve the efficiency of the NSUF technical leads since the PI will be starting with a better statement of work for the project. The tools will also provide resources for NSUF staff to more efficiently screen and score incoming proposals. This implementation plan will layout the work breakdown structure, activities, resources required, and plan for completion of the activities for CoMET in FY2019.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling the Effective Elasticity of Anisotropic Porous Materials

The development and optimization of composite materials designed for thermal protection of NASA’s spacecraft require understanding their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the microscale on realistic representations of these composites. The digital microstructures are generated either synthetically or through X-ray micro-computed tomography reconstructions. One of the main challenges in the prediction of the structural response of heatshield materials is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the microscale. These are driven by the fiber layout within the microstructure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled using a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA) that was presented at the 10th Ablation Workshop. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases, and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.

Elasticity↗

Hydrogen Energy Storage Integrated with a Combined Cycle Plant

A project is being developed that will build upon the existing infrastructure and resources at the Intermountain Power Project (IPP) site to provide reliable, dispatchable energy and to support the transmission of renewable energy resources while transitioning to an economical green energy future. The concept study depicted in this report outlines a techno-economic optimization to fulfill the demand for 30% vol hydrogen co-firing in the IPP 840 MW advanced class combined cycle power plant. In an initial step, a site assessment concluded the site has sufficient land available to co-locate a hydrogen production and storage facility. The team evaluated and defined a scalable concept that considered technology characteristics, including input and output models to be used for optimization purposes. The concept for the hydrogen production and storage system integrates multiple technologies, to determine system size and scalable approach, for each of the technologies evaluated, the team defined component and subcomponent sizes, minimum and maximum capacity, modularity, component utility consumption (electric, water), component flexibility and servicing, layout, and technology status, as well as technology alternatives. For hydrogen generation, the project considers Siemens Energy’s Silyzer-300 (S300) technology, a 17.5 MW modular Proton Exchange Membrane (PEM) electrolyzer. For the S300 configuration, the team determined that three S300 arrays, or approximately 1,000 kg/hr, per block would yield a compact block design. This configuration results in a fairly wide and flexible arrangement that fits well into the spaces available at the site. Therefore, the overall design approach is based on multiple identical blocks of 3 arrays to minimize engineering cost and optimize constructability. In parallel, a transmission screening study was conducted to determine any potential transmission constraints from the energy sources that could feed the hydrogen production equipment. The study results show that minimum transmission constraints would be encountered to deliver 400 MW renewable generation from southern California, or south-central Wyoming. At last, the techno-economic analysis concluded that a scenario that uses solar and wind power yields the lowest levelized cost of hydrogen (LCOH 2 ) production and the lowest cost per tonne of CO 2 reduced. In this optimized scenario, the hydrogen production plant was determined as 6,201 kg/hr and the hydrogen storage (underground cavern) was determined as 4,600 tonnes. The resulting capacity factor for the hydrogen production plant was 66.33% with 8,745 operating hours in one year. This techno-economic analysis provided various options for integrating hydrogen storage at the Intermountain Power Plant site to co-fire the CCPP units. The results provide insightful data about the magnitude of capacity needed and the economics of producing hydrogen and reducing CO 2 emissions.

08 HYDROGEN↗

Computing the effective elasticity of anisotropic porous media from X-ray computed micro-tomography images

Development and optimization of composite materials designed for thermal protection of NASA’s spacecraft requires the understanding of their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the micro-scale on realistic representations of these composites. The digital micro-structures are generated either synthetically or through X-ray micro-tomography reconstructions. One of the main challenges in the prediction of heatshield material structural response is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the micro-scale. These are driven by the fiber layout within the micro-structure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled through the use of a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme. The MPSA, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA), was discussed in a previous presentation at the 15th USCCN and in reference. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.

Federico Semeraro↗

From Detector Layout to Signal Analysis: Geometry Optimization and Neutron-Gamma Tagging in Plastic Scintillator Detectors

Neutrinos are elementary particles with many properties still unknown. Their masses so far have only upper and lower limits. Still, due to neutrino oscillations, it is clear that they are not massless, as stated by the Standard Model of Elementary Particles. Neutrinos are also present in the Universe in vast amounts, but they rarely interact with the surrounding matter. Their abundance makes them very interesting for many theories beyond the Standard Model, e.g., dark matter searches and CP symmetry violation in the leptonic sector, which could be (partially) responsible for the observed matter-antimatter asymmetry in today's Universe.\\ The Deep Underground Neutrino Experiment (DUNE) is a next-generation accelerator-based neutrino oscillation experiment that will study neutrinos with unprecedented precision and may answer many open questions. DUNE uses a powerful neutrino beam from Fermilab. It consists of a Near Detector (ND) complex to measure neutrinos before oscillat ion, and a Far Detector (FD) complex $1300\ \mathrm{km}$ away to measure them after oscillation. As part of the ND complex, measurements are also possible with different angles to the neutrino beam. This enables excellent control of systematic uncertainties of e.g., neutrino cross section measurements.\\ One detector in the near detector complex is The Muon Spectrometer (TMS), an extension of a Liquid Argon (LAr) detector that measures the charge and momentum of muons produced in neutrino interactions within the LAr. The design of this detector, which consists of alternating layers of steel and plastic scintillator bars, must be optimized for the expected muon energies.\\ In this thesis, a study of the optimal module orientation plan is presented, which is necessary for the physics performance of the near detector complex and, by extension, DUNE. As part of this study, the event reconstruction was also developed and improved. Simulated muons are then reconstructed, and the performan ce of different module orientation plans is tested.\\ As a second part, a study of neutron and gamma tagging using a Pulse Shape Discriminating (PSD) plastic scintillator is presented. The properties of this material allow particle differentiation based on the temporal distribution of emitted light. A novel approach to using the individual light signals was successfully tested using data from a small, local test setup.

Nehm, Asa [Mainz U.]↗

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗

Engine Power Turbine and Propulsion Pod Arrangement Study

A study has been conducted for NASA Glenn Research Center under contract NNC10BA05B, Task NNC11TA80T to identify beneficial arrangements of the turboshaft engine, transmissions and related systems within the propulsion pod nacelle of NASA's Large Civil Tilt-Rotor 2nd iteration (LCTR2) vehicle. Propulsion pod layouts were used to investigate potential advantages, disadvantages, as well as constraints of various arrangements assuming front or aft shafted engines. Results from previous NASA LCTR2 propulsion system studies and tasks performed by Boeing under NASA contracts are used as the basis for this study. This configuration consists of two Fixed Geometry Variable Speed Power Turbine Engines and related drive and rotor systems (per nacelle) arranged in tilting nacelles near the wing tip. Entry-into-service (EIS) 2035 technology is assumed for both the engine and drive systems. The variable speed rotor system changes from 100 percent speed for hover to 54 percent speed for cruise by the means of a two speed gearbox concept developed under previous NASA contracts. Propulsion and drive system configurations that resulted in minimum vehicle gross weight were identified in previous work and used here. Results reported in this study illustrate that a forward shafted engine has a slight weight benefit over an aft shafted engine for the LCTR2 vehicle. Although the aft shafted engines provide a more controlled and centered CG (between hover and cruise), the length of the long rotor shaft and complicated engine exhaust arrangement outweighed the potential benefits. A Multi-Disciplinary Analysis and Optimization (MDAO) approach for transmission sizing was also explored for this study. This tool offers quick analysis of gear loads, bearing lives, efficiencies, etc., through use of commercially available RomaxDESIGNER software. The goal was to create quick methods to explore various concept models. The output results from RomaxDESIGNER have been successfully linked to Boeing spreadsheets that generate gear tooth geometry in Catia 3D environment. Another initial goal was to link information from RomaxDESIGNER (such as hp, rpm, gear ratio) to populate Boeing's parametric weight spreadsheet and create an automated method to estimate drive system weight. This was only partially achieved due to the variety of weight models, number of manual inputs, and qualitative assessments required. A simplified weight spreadsheet was used with data inputs from RomaxDESIGNER along with manual inputs to perform rough weight calculations.

Robuck, Mark↗

Optimization of an enclosed gas analyzer sampling system for measuring eddy covariance fluxes of H 2 O and CO 2

Several initiatives are currently emerging to observe the exchange of energy and matter between the earth's surface and atmosphere standardized over larger space and time domains. For example, the National Ecological Observatory Network (NEON) and the Integrated Carbon Observing System (ICOS) are set to provide the ability of unbiased ecological inference across ecoclimatic zones and decades by deploying highly scalable and robust instruments and data processing. In the construction of these observatories, enclosed infrared gas analyzers are widely employed for eddy covariance applications. While these sensors represent a substantial improvement compared to their open- and closed-path predecessors, remaining high-frequency attenuation varies with site properties and gas sampling systems, and requires correction. Here, we show that components of the gas sampling system can substantially contribute to such high-frequency attenuation, but their effects can be significantly reduced by careful system design. From laboratory tests we determine the frequency at which signal attenuation reaches 50 % for individual parts of the gas sampling system. For different models of rain caps and particulate filters, this frequency falls into ranges of 2.5–16.5 Hz for CO 2 , 2.4–14.3 Hz for H 2 O, and 8.3–21.8 Hz for CO 2 , 1.4–19.9 Hz for H 2 O, respectively. A short and thin stainless steel intake tube was found to not limit frequency response, with 50 % attenuation occurring at frequencies well above 10 Hz for both H 2 O and CO 2 . From field tests we found that heating the intake tube and particulate filter continuously with 4 W was effective, and reduced the occurrence of problematic relative humidity levels (RH > 60 %) by 50 % in the infrared gas analyzer cell. No further improvement of H 2 O frequency response was found for heating in excess of 4 W. These laboratory and field tests were reconciled using resistor–capacitor theory, and NEON's final gas sampling system was developed on this basis. The design consists of the stainless steel intake tube, a pleated mesh particulate filter and a low-volume rain cap in combination with 4 W of heating and insulation. In comparison to the original design, this reduced the high-frequency attenuation for H 2 O by ≈ 3/4, and the remaining cospectral correction did not exceed 3 %, even at high relative humidity (95 %). The standardized design can be used across a wide range of ecoclimates and site layouts, and maximizes practicability due to minimal flow resistance and maintenance needs. Lastly, due to minimal high-frequency spectral loss, it supports the routine application of adaptive correction procedures, and enables largely automated data processing across sites.

54 ENVIRONMENTAL SCIENCES↗

X-ray diagnostic developments in the perspective of DEMO

Soft X-ray diagnostics at present are not adequate for a burning plasma experiment, neither in term of hardware nor as diagnostic conception. Detectors have to be radiation tolerant, easily shielded, with low sensitivity to neutrons and gammas and with energy discrimination. Layout and viewing capability should be more flexible, thanks to the use also of optical devices, going toward a configuration intermediate between discrete tomography and pure imaging. The general conception of these diagnostics should therefore evolve in the direction of pattern recognition for a real time feedback. This work is focused on the diagnostic developments undertaken at the ENEA- Frascati X-ray Laboratory, following in particular three directions: gas detector for fast and advanced high density tomography, C-MOS solid state imaging detectors for slow control and X-ray polycapillary optics. GEM gas detectors in photon counting mode (noise free) were developed in the range 1-30 keV having high efficiency, high time resolution (up to microseconds), energy discrimination in bands and optical flexibility. Discrimination of X-rays, neutrons and gammas has been demonstrated, thanks to the combination of intrinsic gain and discrimination thresholds, at neutron fluxes (10{sup 7} n/s*cm{sup 2}) comparable with the expected ones at the ports of ITER. GEM detectors are also extremely flexible in the design, allowing optimization of the measurements and solutions for shielding or minimization of the effect of background radiation. Two solid state C-MOS imagers working in photon counting mode, one based on Si semiconductor (Medipix-2, range 5-30 keV) and the other one having a CdTe sensor (Pixirad, range 2-100 keV) have been characterized in laboratory. C-MOS imagers have features and performances thoroughly complementary to the GEM detector and, thanks to their higher pixel density, could be used as remote imaging detectors coupled to optics. X-ray polycapillary lenses have been therefore studied in the laboratory both as imaging optical device (full lens) or to define a line of sight (cylinder lens); the preliminary results are encouraging toward the goal of using these lenses to transport X-ray radiation far from the reactor. Reflective or diffractive X-ray optics can be also an option for tomography. A GEM detector has been installed at KSTAR and in the next future hopefully the other approaches will be tested there: once their feasibility will be demonstrated, the issue of the improvement of the radiation tolerance will be faced and the development of algorithms for data analysis as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Prefabricated High-Strength Rebar Systems with High-Performance Concrete for Accelerated Construction of Nuclear Concrete Structures

This project aimed to reduce the field construction times and fabrication costs of reinforced concrete (RC) nuclear structures through the use of: 1) high-strength steel deformed reinforcing bar (rebar); 2) prefabricated high-strength rebar (HSR) assemblies with headed anchorages; and 3) high-strength concrete (HSC). The focus of the project was not to develop new innovations on materials, but rather to fill a major knowledge gap on the effectiveness, code conformity, and viability (i.e., practicality, commercial availability) of existing high-strength materials in nuclear structures, especially in shear walls, their connections/joints, and around penetrations. These advances promote the Nuclear Energy Enabling Technologies Advanced Methods for Manufacturing (NEET-1) goals of accelerating deployment schedules by at least 6 months and reducing component fabrication costs by 20% or more. Toward this vision, the following objectives were identified and completed: Develop limit-benefit and cost-benefit analysis frameworks: The structural and economic limits and benefits of HSR and HSC in nuclear walls were evaluated. Importantly, it was found that modest increases in concrete strength up to 10.0 ksi and rebar yield strength up to 100 ksi result in the most economic designs and improved structural performance (Barbachyn et al., 2017a and Barbachyn et al., 2017b). Also, an industry survey was distributed to determine the cost benefits associated with prefabrication. Importantly, on-site worker-hours are significantly reduced, allowing for significantly accelerated construction schedules (Devine et al. 2018b). Develop an optimization methodology for structural design: An optimization study was deemed not necessary since the trivial solution with maximized use of high-strength materials and prefabrication always resulted in the largest cost and time savings. Instead, the benefits (and limits) of high-strength materials and prefabrication on construction costs and on-site construction time were investigated through a parametric study. Cost-reductions through the use of HSR and HSC were found to be greater than 40%. Also, on-site construction time of nuclear shear walls can be reduced by up to 83% through the use of prefabricated rebar assemblies. Conduct experimental evaluations of nuclear shear walls and wall-foundation joints: A large scale experimental program was completed on shear-critical RC cantilever deep beams. From these experiments, it was demonstrated that increasing rebar yield strength had a greater effect on increasing lateral strength than increasing the concrete compressive strength. Further, using HSR together with HSC resulted in the highest lateral strength and displacement ductility (Devine et al. 2018a). Additionally, large-scale reversed-cyclic lateral load tests were conducted on RC shear walls. It was demonstrated that through the utilization of HSR and HSC, a wall with 55% reduced vertical and horizontal rebar area was able to achieve 91% of the peak lateral strength of a conventional wall using state-of-practice materials with the same geometry. Further, trim reinforcement with headed anchorages around the penetrations proved to be effective. Develop validated numerical simulation models: Numerical modeling was completed in two phases during this project using 3 different finite element software packages. The first phase used existing measured data from previous experimental studies on stocky RC walls to validate simplified predictive models. Models using two different programs were validated based on a database of 38 stocky walls (Barbachyn et al., 2017a). The second phase occurred after experimental testing using a third and more detailed finite element package. Prediction improvements for the initial stiffness, lateral deformations, damage propagation, and failure mechanisms were targeted. The resulting detailed models more accurately predicted the peak lateral strength, initial and secant stiffnesses, lateral deformations, and cracking patterns of the wall test specimens subjected to reversed-cyclic lateral loading as compared to the simplified pretest models. Develop validated design procedures, tools, and criteria: This project evaluated the accuracy of existing closed-form design equations from U.S. building design standards and previous research (Barbachyn et al. 2017a and Devine et al. 2018a). It was shown that the current predictive equations for shear strength capacity need to be revisited as they provide significant scatter and gross overestimates, indicating the potential for unconservative designs. Further, for both the deep beam and shear wall specimens, the numerical models and flexural capacity predictions provided the most accurate strength predictions. Develop cost-effective field construction procedures: To promote the use of prefabricated rebar assemblies, the following construction conditions where prefabrication would be used instead of in-place rebar tying were identified from an industry survey: 1) to save on construction schedule; 2) to improve safety and/or quality control; 3) for areas with heavy rebar congestion; and 4) for structures with significant repetition in rebar layout. All of these conditions directly apply and benefit nuclear construction where construction costs and schedules are extensive, safety and quality are of utmost importance, the reinforcement is extremely dense, and the reinforcement layout is repetitive in many regions of the shear walls. Additionally, an experimental study was conducted to investigate the changes in bar spacing (with respect to code-required rebar spacing and placement tolerances) when a horizontally assembled prefabricated two-dimensional (2D) rebar mat or three-dimensional (3D) rebar cage is lifted (or tripped) to a vertical position. It was found that the bars involved in both the lateral translation of the rebar assemblies (i.e., movement of the assembly in its horizontal position) and the tripping process were most susceptible to large spacing changes, and thus, their positions within the assembly would need to be checked after the placement of the assembly in place within the formwork. Importantly, the spacings of all of the other bars in the assembly were not affected significantly by the lateral translation and tripping process, thereby eliminating the need to recheck their positions within the assembly (Devine et al. 2018b).

36 MATERIALS SCIENCE↗