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At least 631 records · Page 35

Implementation and Assessment of Menter’s Galilean-Invariant γ Transition Model in OVERFLOW

With an increased emphasis on greener air transports and sustainable aviation, the modeling of laminar-to-turbulent boundary layer transition is anticipated to have an added significance, particularly in the applications related to laminar flow technology. However, unmanned aerial vehicles, crewed reentry vehicles, and ground-to-flight extrapolation all benefit from transition models. Because no single transition model is ideal for the complete spectrum of applications, it is useful to incorporate a variety of models in general-purpose CFD solvers, such as the NASA OVERFLOW Overset CFD code. While the Langtry-Menter 𝛄 − 𝑹𝒆 𝛉𝒕 model, currently available in OVERFLOW, has been widely used for CFD predictions of flows with laminar, transitional, and turbulent boundary layers, it does not possess the Galilean invariance property, a desirable attribute for rotorcraft applications. To help overcome that limitation, we have recently implemented Menter's baseline version of the SST-based γ transition model, along with a Galilean invariant stationary crossflow extension within OVERFLOW (version 2.3e). An initial assessment of the newly implemented model has been carried out using 2D benchmark cases including flat plates and the NLF-0416 airfoil, addressing several transition scenarios ranging from bypass transition due to freestream turbulence, natural transition via Tollmien-Schlichting instabilities, and transition due to a laminar separation bubble. The crossflow extension has been applied to the infinite swept NLF(2)-0415 wing and the 6:1 prolate spheroid. Wherever possible, the results were obtained on a sequence of meshes to ascertain the grid convergence behavior, which has been evaluated through global metrics such as force coefficients as well as local values of the skin-friction coefficient at selected points near and within the transition region. Overall, the model appears to be correctly implemented and the results show promise for further development using the framework of the γ transition model.

CFD modeling↗

Radiative Heat Transfer Capability Implemented in OpenNCC for Conjugate Heat Transfer Applications

Thermal efficiency of gas turbine engine increases as the temperature and pressure at the combustor increases. Consequently, the materials used inside a combustor must survive an increasingly challenging environment. For this reason, accurate assessment of heat transfer is crucial for combustor design. While all three modes of heat transfer are present inside a combustor, the focus of this paper is the thermal radiation. Radiative heat transfer in a gas turbine combustors are particularly interesting from three reasons. Firstly, the radiative heat loss from the combustion region may affect the emission performance. Secondly, the cooling air will protect the liner from convection but not necessary from radiation. Finally, it is less frequently incorporated in CFD analysis than other forms of heat transfer. In this work, radiative heat transfer using discrete ordinate method has been incorporated in OpenNCC (a publicly releasable version of the National Combustion Code) developed at NASA Glenn Research Center. Aside from massively parallel computation capability using MPI and the ability to utilize unstructured mesh, the current implementation includes two types of spectral models, namely, the weighted some of gray gas model and the full spectrum correlated k-distribution model. After presenting the theory and the strategy of implementation, results of validation cases for gray gas and spectral models will be presented. While the implementation of the radiation solver is intended for gas turbine application, the radiation solver can run independently from the convection/combustion solver and the same theory can be applied to other application.

OpenNCC↗

Radiative Heat Transfer Capability Implemented in OpenNCC for Conjugate Heat Transfer Applications

Thermal efficiency of gas turbine engine increases as the temperature and pressure at the combustor increases. Consequently, the materials used inside a combustor must survive an increasingly challenging environment. For this reason, accurate assessment of heat transfer is crucial for combustor design. While all three modes of heat transfer are present inside a combustor, the focus of this paper is the thermal radiation. Radiative heat transfer in a gas turbine combustors are particularly interesting from three reasons. Firstly, the radiative heat loss from the combustion region may affect the emission performance. Secondly, the cooling air will protect the liner from convection but not necessary from radiation. Finally, it is less frequently incorporated in CFD analysis than other forms of heat transfer. In this work, radiative heat transfer using discrete ordinate method has been incorporated in OpenNCC (a publicly releasable version of the National Combustion Code) developed at NASA Glenn Research Center. Aside from massively parallel computation capability using MPI and the ability to utilize unstructured mesh, the current implementation includes two types of spectral models, namely, the weighted some of gray gas model and the full spectrum correlated k-distribution model. After presenting the theory and the strategy of implementation, results of validation cases for gray gas and spectral models will be presented. While the implementation of the radiation solver is intended for gas turbine application, the radiation solver can run independently from the convection/combustion solver and the same theory can be applied to other application.

OpenNCC↗

Evaluation of a Regional Crop Model Implementation for Sub-National Yield Assessments in Kenya

CONTEXT: Cropping system models can be used to both assess regional food security and to monitor and predict agricultural drought. Agriculture in Kenya is extremely important to both the economy and food security of the country. OBJECTIVE: This study evaluated a regional implementation of a widely used crop model, the Decision Support System for Agrotechnology Transfer (DSSAT), within a coupled modeling framework, the Regional Hydrologic Extremes Assessment System (RHEAS), over Kenya. The goal of this study was to assess the ability of RHEAS to simulate the annual variability of maize yields at the county level and evaluate the uncertainty inherent in the model and inputs. METHODS: The RHEAS system implements a stochastic ensemble approach to account for field scale variabilities in crop management practices and underlying soil and weather conditions. Satellite-derived datasets were used to evaluate the land surface component of the system and seasonally disaggregated yield for 5 years was used to assess the performance of the cropping system model. RESULTS AND CONCLUSIONS: The median correlation between RHEAS and satellite-derived soil moisture and evapotranspiration estimates were 0.78, and 0.51, respectively, indicating that the model is able to capture the key drivers of the hydrological budget. Overall, RHEAS simulated yearly yield variations with a median correlation of 0.7 with reported yields, with the best performance in the short rains season. However, across both seasons, the RHEAS model was positively biased on the order of ~1.6 MT/ha. The overall median unbiased RMSE was 0.66 MT/ha. The RHEAS system shows skill at simulating extreme departures in anomalies, and a majority of the time (62.5%) the reported yields fall within the interquartile range of the simulations. SIGNIFICANCE: One of the most important areas of improvement for the next generation of agricultural data and models is to better understand and communicate the inherent uncertainties. This is especially critical in data-limited regions. Here we present a modeling system and its implementation that begins to address these concerns. We demonstrate the ability to simulate broad trends in yields at the county level for sub-annual yields with skills that commensurate previous national/annual level studies.

Crop model↗

Implementation of Interactive Sea Ice Radiative Transfer into the GISS GCM and Its Impact on Sea Ice Simulation

To improve the representation of solar radiation in sea ice in the Goddard Institute for Space Studies (GISS) climate model (ModelE), we have implemented an advanced radiative transfer (RT) scheme to interactively calculate the surface albedo and transmittance of the ice layer and the solar absorption within. The ice physical properties (temperature, salinity, and density), which are simulated by the thermodynamic module in ModelE, are directly used as the input of the RT scheme to determine the inherent optical properties (IOPs) of brine pockets and air bubbles in the ice layers. This provides a more sophisticated, accurate, and complete treatment of sea ice RT for ModelE. The sea ice RT model is also validated with measured spectral albedo and transmittance for different ice types. Compared with ModelE simulations with current radiative parameterization for sea ice, the new RT implementation will slightly increase the ice surface albedo in the summer in the Arctic and greatly increase the radiative transmittance. Consequently, the ice surface melting is reduced and the base melting is increased but the difference in the simulated ice area is small. The effect of this new RT implementation on the Antarctic ice is negligible. The observed decrease in Arctic sea ice extent is well captured by the ModelE simulation.

Sea ice↗

Field-Programmable Gate Array Implementation of a Single Photon-Counting Receive Modem

We present a field-programmable gate array (FPGA) implementation of a single photon-counting receive modem for a pulse position modulated signal. The modem is compliant with the Consultative Committee for Space Data Systems (CCSDS) High Photon Efficiency (HPE) Optical Communications Coding and Synchronization standard and is capable of a maximum data rate of 267 Mbps. The system is designed on a commercial off-the-shelf FPGA platform and utilizes superconducting nanowire single photon counting detectors, analog to digital converters (ADC s) to sample the detectors, and two FPGAs. Symbol timing recovery, photon counting, convolutional deinterleaving, and codeword synchronization areis performed in the first FPGA. The second FPGA performs iterative decoding on each codeword of the serially concatenated pulse position modulated (SCPPM) signal. A digital filter is included to compensate for timing jitter of the detector, and the decoder throughput can be modified adjusted through reconfigurable parallelization. The decoder also implements a resource-efficient, algorithmic polynomial interleaver and deinterleaver. Both FPGAs can be reconfigured to switch between pulse position modulation (PPM)-16 and PPM-32 with code rates 1/3, 1/2, and 2/3. In this paper, we describe the receiver architecture and FPGA implementation of the timing recovery loop and SCPPM decoder, FPGA utilization for the different modes, and receive modem characterization test results.

Field-programmable Gate Array↗

2022 Through April 2023 Corrective Measures Implementation and Interim Measures Annual Status Report: Summary of Biosparge System Operation and Maintenance, Interim Measures and Monitoring Mobile Launch Platform Rehabilitation Sites / Vehicle Assembly Building Area (Swmu 056) Kennedy Space Center, Florida

This report presents a summary of the Corrective Measures Implementation (CMI) and Interim Measure (IM) implementation activities that occurred from January 2022 through April 2023 at the Mobile Launch Platform Rehabilitation Sites (MLP)/Vehicle Assembly Building (VAB) Area, Solid Waste Management Unit 056 (SWMU 056), located at the John F. Kennedy Space Center, Florida. The following summaries briefly describe areas within SWMU 056 identified by historical site investigation activities where groundwater monitoring and remedial actions have been implemented to date.

VOCs↗

Managing Current Earth Observation Needs through User-Driven Implementation of Upcoming Satellite Needs Working Group (SNWG) Solutions

Since 2016, the Satellite Needs Working Group (SNWG), an initiative of the U.S. Group on Earth Observations (USGEO), has surveyed federal agencies every two years to identify their satellite earth observation needs. For each expressed need, NASA-led assessment teams coordinate with responding agencies to devise remote sensing solutions that benefit multiple partners and span across a number of thematic areas including, but not limited to, Atmospheric Composition, Carbon Cycle and Ecosystems, Earth Surface and Interior, and Oceans and Cryosphere. Solutions can comprise existing or modified data products as well as the construction of new data products and technologies: since 2016, a multitude of SNWG activities have been theorized and developed, reaching a wide range of users in the science community. Due to an increase in survey responses in 2020 and to assure solution delivery to users within five years of budget appropriations, the SNWG Management Office was established to oversee the assessment of agency needs and the implementation and operations of solution development. The SNWG MO’s unique implementation strategy creates multiple touchpoints with agencies during solution development helping fulfill Earth Science to Action priorities (the 2024 NASA Earth Science Division strategic plan) and ensuring solutions are accessible, usable, and support decision-making for their intended audience. This presentation will outline the ways in which SNWG supports complementary goals of the Decadal Survey, with specific attention on the SNWG MO’s renewed user-centric implementation strategy for upcoming SNWG solutions.

Jenny Wood↗

Implementation of Recommendations from the One System Comparative Evaluation of the Hanford Tank Farms and Waste Treatment Plant Safety Bases

A Comparative Evaluation was conducted for One System Integrated Project Team to compare the safety bases for the Hanford Waste Treatment and Immobilization Plant Project (WTP) and Tank Operations Contract (TOC) (i.e., Tank Farms) by an Expert Review Team. The evaluation had an overarching purpose to facilitate effective integration between WTP and TOC safety bases. It was to provide One System management with an objective evaluation of identified differences in safety basis process requirements, guidance, direction, procedures, and products (including safety controls, key safety basis inputs and assumptions, and consequence calculation methodologies) between WTP and TOC. The evaluation identified 25 recommendations (Opportunities for Integration). The resolution of these recommendations resulted in 16 implementation plans. The completion of these implementation plans will help ensure consistent safety bases for WTP and TOC along with consistent safety basis processes. procedures, and analyses. and should increase the likelihood of a successful startup of the WTP. This early integration will result in long-term cost savings and significant operational improvements. In addition, the implementation plans lead to the development of eight new safety analysis methodologies that can be used at other U.S. Department of Energy (US DOE) complex sites where URS Corporation is involved.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance

Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric demand against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed calculations. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed predictions. We focused on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

System, apparatus and methods to implement high-speed network analyzers

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

42 ENGINEERING↗

Open SHMEM Reference Implementation

OpenSHMEM is an effort to create a specification for a standardized API for parallel programming in the Partitioned Global Address Space. Along with the specification the project is also creating a reference implementation of the API. This implementation attempts to be portable, to allow it to be deployed in multiple environments, and to be a starting point for implementations targeted to particular hardware platforms. It will also serve as a springboard for future development of the API.

Pritchard, Howard↗

IMPLEMENTATION OF THE IMPROVED QUASI-STATIC METHOD IN RATTLESNAKE/MOOSE FOR TIME-DEPENDENT RADIATION TRANSPORT MODELLING

Because of the recent interest in reactor transient modeling and the restart of the Transient Reactor (TREAT) Facility, there has been a need for more efficient, robust methods in computation frameworks. This is the impetus of implementing the Improved Quasi-Static method (IQS) in the RATTLESNAKE/MOOSE framework. IQS has implemented with CFEM diffusion by factorizing flux into time-dependent amplitude and spacial- and weakly time-dependent shape. The shape evaluation is very similar to a flux diffusion solve and is computed at large (macro) time steps. While the amplitude evaluation is a PRKE solve where the parameters are dependent on the shape and is computed at small (micro) time steps. IQS has been tested with a custom one-dimensional example and the TWIGL ramp benchmark. These examples prove it to be a viable and effective method for highly transient cases. More complex cases are intended to be applied to further test the method and its implementation.

IQS↗

Method for implementing depth deconvolution algorithm for enhanced thermal tomography 3D imaging

A computer-implemented method, apparatus, and computer program product implement enhanced thermal tomography three-dimensional (3D) thermal effusivity imaging. Experimental thermal imaging data is acquired. A response function is derived and a convolution formulation is constructed from the experimental thermal imaging data. A deconvolution solution procedure is implemented that includes constructing a matrix solution equation with a damping parameter, and solving the matrix solution equation with a selected number of iterations to construct a plurality of effusivity images. Using the novel depth deconvolution algorithm with experimental data acquired from a one-sided pulsed thermal-imaging system provides greater sensitivity for internal sample features substantially eliminating degradation in depth resolution.

36 MATERIALS SCIENCE↗

Enhancing Operational Performance and Productivity Benefits by Implementing Smart Manufacturing Technologies in Breweries

This paper uses case studies to demonstrate the potential of smart manufacturing (SM) and Internet of Things (IoT) technologies to enhance operational performance and productivity in the industry. The analysis highlights benefits like cost reduction, production flexibility, shorter product times-to-market, energy/water efficiency and environmental impact reduction, and increased productivity. To illustrate the effectiveness of SM and IoT approaches, the authors sought out manufacturers currently implementing or seeking to implement SM & IoT technologies. The authors identified beer brewing (NAICS Code —312120) as a rapidly expanding industry whose members appear eager to implement SM technologies to optimize production lines by revealing bottlenecks and identifying performance-reducing nodes. The paper presents two case studies based on SM and IoT technologies in breweries. It briefly describes a systematic framework introduced elsewhere by the authors and uses it to assess the energy productivity and competitiveness of SM applications in breweries. The paper addresses questions concerning the information and communications technology infrastructure needed to build smart breweries, and how corporations simplify the installation and deployment of SM and IoT components.

Nimbalkar, Sachin U.↗

On the Efficacy and High-Performance Implementation of Quaternion Matrix Multiplication

Quaternion symmetry is ubiquitous in the physical sciences. As such, much work has been afforded over the years to the development of efficient schemes to exploit this symmetry using real and complex linear algebra. Recent years have also seen many advances in the formal theoretical development of explicitly quaternion linear algebra with promising applications in image processing and machine learning. Despite these advances, there do not currently exist optimized software implementations of quaternion linear algebra. The leverage of optimized linear algebra software is crucial in the achievement of high levels of performance on modern computing architectures, and thus provides a central tool in the development of high-performance scientific software. In this work, a case will be made for the efficacy of high-performance quaternion linear algebra software for appropriate problems. In this pursuit, an optimized software implementation of quaternion matrix multiplication will be presented and will be shown to outperform a vendor tuned implementation for the analogous complex matrix operation. The results of this work pave the path for further development of high-performance quaternion linear algebra software which will improve the performance of the next generation of applicable scientific applications.

97 MATHEMATICS AND COMPUTING↗

Enhancing the Implementation of a First-order Equivalent Thermal Parameter Model to Enable Accurate and Robust Building Thermal Response Prediction

Predicting indoor temperature conditions are often necessary for advanced building controls. Gray-box models are preferable to do so because they can over- come limitations of white-box and black-box models; however, their current implementation methods can be problematic due to their difficulties in capturing non-linear behaviors and time-varying disturbances. This paper proposes a novel method to implement a popular gray-box model, the 1st-order equivalent thermal parameter (ETP) model. To evaluate performance, we applied the proposed method to predict in- door temperatures for a medium-office building, over the course of one day. Predictions are compared against two existing methods: the ETP model implemented through a common approach and a black-box model. Results suggest that the proposed method can yield more accurate results compared to the other methods; additionally, the proposed method demonstrated similar capabilities in capturing non-linear behaviors as the black-box model.

Hinkelman, Kathryn↗

Considerations for Safeguards Implementation in the Post-Operational Facility Life Cycle

Hundreds of facilities around the world under International Atomic Energy Agency (IAEA) safeguards are currently permanently shutdown or undergoing decommissioning. For facilities in States with a comprehensive safeguards agreement (CSA) in force, safeguards obligations under the CSA extend until the IAEA has determined for safeguards purposes that a facility has been decommissioned (i.e., the IAEA has verified that the nuclear material has been removed and residual structures and equipment essential for its use have been removed or rendered inoperable). The IAEA Department of Safeguards recently issued a report providing high-level guidance to States on IAEA safeguards implementation throughout the post-operational life cycle phases of facilities and locations outside facilities. These phases include permanent shutdown, closed-down, and decommissioned for safeguards purposes. Additional consideration is needed for how post-operational facilities might be consistently evaluated when developing State-level safeguards approaches. This work presents ideas about how the IAEA might implement the State-level concept and associated elements (e.g., State-specific factors) throughout the post-operational life cycle, focusing on maintaining effectiveness and gaining efficiencies where appropriate. Considerations include whether State-specific factors should influence facility status, how a change in a facility’s post-operational status might impact a State’s acquisition path analysis, and how rendering inoperable/removal of essential equipment could affect resources expended on safeguards implementation.

Hogue, Karen↗