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At least 775 records · Page 43

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗

Performance analysis of a large-grain dataflow scheduling paradigm

A paradigm for scheduling computations on a network of multiprocessors using large-grain data flow scheduling at run time is described and analyzed. The computations to be scheduled must follow a static flow graph, while the schedule itself will be dynamic (i.e., determined at run time). Many applications characterized by static flow exist, and they include real-time control and digital signal processing. With the advent of computer-aided software engineering (CASE) tools for capturing software designs in dataflow-like structures, macro-dataflow scheduling becomes increasingly attractive, if not necessary. For parallel implementations, using the macro-dataflow method allows the scheduling to be insulated from the application designer and enables the maximum utilization of available resources. Further, by allowing multitasking, processor utilizations can approach 100 percent while they maintain maximum speedup. Extensive simulation studies are performed on 4-, 8-, and 16-processor architectures that reflect the effects of communication delays, scheduling delays, algorithm class, and multitasking on performance and speedup gains.

Young, Steven D.↗

Multi-Point Combustion System: Final Report

A low-NOx emission combustor concept has been developed for NASA's Environmentally Responsible Aircraft (ERA) program to meet N+2 emissions goals for a 70,000 lb thrust engine application. These goals include 75 percent reduction of LTO NOx from CAEP6 standards without increasing CO, UHC, or smoke from that of current state of the art. An additional key factor in this work is to improve lean combustion stability over that of previous work performed on similar technology in the early 2000s. The purpose of this paper is to present the final report for the NASA contract. This work included the design, analysis, and test of a multi-point combustion system. All design work was based on the results of Computational Fluid Dynamics modeling with the end results tested on a medium pressure combustion rig at the UC and a medium pressure combustion rig at GRC. The theories behind the designs, results of analysis, and experimental test data will be discussed in this report. The combustion system consists of five radially staged rows of injectors, where ten small scale injectors are used in place of a single traditional nozzle. Major accomplishments of the current work include the design of a Multipoint Lean Direct Injection (MLDI) array and associated air blast and pilot fuel injectors, which is expected to meet or exceed the goal of a 75 percent reduction in LTO NOx from CAEP6 standards. This design incorporates a reduced number of injectors over previous multipoint designs, simplified and lightweight components, and a very compact combustor section. Additional outcomes of the program are validation that the design of these combustion systems can be aided by the use of Computational Fluid Dynamics to predict and reduce emissions. Furthermore, the staging of fuel through the individually controlled radially staged injector rows successfully demonstrated improved low power operability as well as improvements in emissions over previous multipoint designs. Additional comparison between Jet- A fuel and a hydrotreated biofuel is made to determine viability of the technology for use with alternative fuels. Finally, the operability of the array and associated nozzles proved to be very stable without requiring additional active or passive control systems. A number of publications have been publish

Goeke, Jerry↗

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

Small solar thermal power systems (up to 10 MWe in size) were tested. The solar thermal power plant ranking study was performed to aid in experiment activity and support decisions for the selection of the most appropriate technological approach. The cost and performance were determined for insolation conditions by utilizing the Solar Energy Simulation computer code (SESII). This model optimizes the size of the collector field and energy storage subsystem for given engine generator and energy transport characteristics. The development of the simulation tool, its operation, and the results achieved from the analysis are discussed.

Rosenberg, L. S.↗

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

Ortiz, C. J.↗

Spatial interpretation of NASA's Marshall Space Flight Center Payload Operations Control Center using virtual reality technology

In its search for higher level computer interfaces and more realistic electronic simulations for measurement and spatial analysis in human factors design, NASA at MSFC is evaluating the functionality of virtual reality (VR) technology. Virtual reality simulation generates a three dimensional environment in which the participant appears to be enveloped. It is a type of interactive simulation in which humans are not only involved, but included. Virtual reality technology is still in the experimental phase, but it appears to be the next logical step after computer aided three-dimensional animation in transferring the viewer from a passive to an active role in experiencing and evaluating an environment. There is great potential for using this new technology when designing environments for more successful interaction, both with the environment and with another participant in a remote location. At the University of North Carolina, a VR simulation of a the planned Sitterson Hall, revealed a flaw in the building's design that had not been observed during examination of the more traditional building plan simulation methods on paper and on computer aided design (CAD) work station. The virtual environment enables multiple participants in remote locations to come together and interact with one another and with the environment. Each participant is capable of seeing herself and the other participants and of interacting with them within the simulated environment.

Lindsey, Patricia F.↗

Design Evolution and Performance Characterization of the GTX Air-Breathing Launch Vehicle Inlet

The design and analysis of a second version of the inlet for the GTX rocket-based combine-cycle launch vehicle is discussed. The previous design did not achieve its predicted performance levels due to excessive turning of low-momentum comer flows and local over-contraction due to asymmetric end-walls. This design attempts to remove these problems by reducing the spike half-angle to 10- from 12-degrees and by implementing true plane of symmetry end-walls. Axisymmetric Reynolds-Averaged Navier-Stokes simulations using both perfect gas and real gas, finite rate chemistry, assumptions were performed to aid in the design process and to create a comprehensive database of inlet performance. The inlet design, which operates over the entire air-breathing Mach number range from 0 to 12, and the performance database are presented. The performance database, for use in cycle analysis, includes predictions of mass capture, pressure recovery, throat Mach number, drag force, and heat load, for the entire Mach range. Results of the computations are compared with experimental data to validate the performance database.

DeBonis, J. R.↗

Stepwise approach to SNP-set analysis illustrated with the Metabochip and colorectal cancer in Japanese Americans of the Multiethnic Cohort

Background: Common variants have explained less than the amount of heritability expected for complex diseases, which has led to interest in less-common variants and more powerful approaches to the analysis of whole-genome scans. Because of low frequency (low statistical power), less-common variants are best analyzed using SNP-set methods such as gene-set or pathway-based analyses. However, there is as yet no clear consensus regarding how to focus in on potential risk variants following set-based analyses. We used a stepwise, telescoping approach to analyze commonand rare-variant data from the Illumina Metabochip array to assess genomic association with colorectal cancer (CRC) in the Japanese sub-population of the Multiethnic Cohort (676 cases, 7180 controls). We started with pathway analysis of SNPs that are in genes and pathways having known mechanistic roles in colorectal cancer, then focused on genes within the pathways that evidenced association with CRC, and finally assessed individual SNPs within the genes that evidenced association. Pathway SNPs downloaded from the dbSNP database were cross-matched with Metabochip SNPs and analyzed using the logistic kernel machine regression approach (logistic SNP-set kernel-machine association test, or sequence kernel association test; SKAT) and related methods. Results: The TGF-β and WNT pathways were associated with all CRC, and the WNT pathway was associated with colon cancer. Individual genes demonstrating the strongest associations were TGFBR2 in the TGF-β pathway and SMAD7 (which is involved in both the TGF-β and WNT pathways). As partial validation of our approach, a known CRC risk variant in SMAD7 (in both the TGF-β and WNT pathways: rs11874392) was associated with CRC risk in our data. We also detected two novel candidate CRC risk variants (rs13075948 and rs17025857) in TGFBR2, a gene known to be associated with CRC risk. Conclusions: A stepwise, telescoping approach identified some potentially novel risk variants associated with colorectal cancer, so it may be a useful method for following up on results of set-based SNP analyses. Further work is required to assess the statistical characteristics of the approach, and additional applications should aid in better clarifying its utility.

59 BASIC BIOLOGICAL SCIENCES↗

Abstract Machine Models and Proxy Architectures for Exascale Computing

To achieve exascale computing, fundamental hardware architectures must change. The most significant consequence of this assertion is the impact on the scientific and engineering applications that run on current high performance computing (HPC) systems, many of which codify years of scientific domain knowledge and refinements for contemporary computer systems. In order to adapt to exascale architectures, developers must be able to reason about new hardware and determine what programming models and algorithms will provide the best blend of performance and energy efficiency into the future. While many details of the exascale architectures are undefined, an abstract machine model is designed to allow application developers to focus on the aspects of the machine that are important or relevant to performance and code structure. These models are intended as communication aids between application developers and hardware architects during the co-design process. We use the term proxy architecture to describe a parameterized version of an abstract machine model, with the parameters added to elucidate potential speeds and capacities of key hardware components. These more detailed architectural models are formulated to enable discussion between the developers of analytic models and simulators and computer hardware architects. They allow for application performance analysis and hardware optimization opportunities. In this report our goal is to provide the application development community with a set of models that can help software developers prepare for exascale. In addition, through the use of proxy architectures, we can enable a more concrete exploration of how well new and evolving application codes map onto future architectures. This second version of the document addresses system scale considerations and provides a system-level abstract machine model with proxy architecture information.

97 MATHEMATICS AND COMPUTING↗

Image-analysis techniques for determination of morphology and kinematics in arctic sea ice

SAR data have been used to study sea ice with respect to its motion and formation/deformation. With the prospect of the Alaska SAR Facility development in the near future, there is a great need for robust and efficient sea-ice analysis techniques. This paper presents a sea-ice motion analysis technique that can be used for: (1) local motion analysis of a selected ice patch, and (2) a global ice motion over the entire image area. In order to meet the operational speed requirement (over fifty images per day) a sea-ice motion analysis technique has been developed which requires very little human interaction. The proposed technique uses a subset of easily distinguishable features to predict global motion characteristics. The developed technique is applied to two pairs of SEASAT SAR images, one pair with a minor motion of 'ice pack' and another with a larger and discontinuous motion of 'fast ice'. The new approach enables the development of a set of computer-aided tools for feature selection and registration and the implementation of an optimal search strategy for automatic template matching via a motion prediction model.

Lee, Meemong↗

An assessment of finite-element modeling techniques for thick-solid/thin-shell joints analysis

The subject of finite-element modeling has long been of critical importance to the practicing designer/analyst who is often faced with obtaining an accurate and cost-effective structural analysis of a particular design. Typically, these two goals are in conflict. The purpose is to discuss the topic of finite-element modeling for solid/shell connections (joints) which are significant for the practicing modeler. Several approaches are currently in use, but frequently various assumptions restrict their use. Such techniques currently used in practical applications were tested, especially to see which technique is the most ideally suited for the computer aided design (CAD) environment. Some basic thoughts regarding each technique are also discussed. As a consequence, some suggestions based on the results are given to lead reliable results in geometrically complex joints where the deformation and stress behavior are complicated.

Min, J. B.↗

A modernized PDL approach for Ada software development

The desire to integrate newly available, graphically-oriented Computed Aided Software Engineering (CASE) tools with existing software design approaches is changing the way Program Design Language (PDL) or Process Description Language is used for large system development. In the approach documented here, Software Engineers use graphics tools to model the problem and to describe high level software design in diagrams. An Ada-based PDL is used to document low level design. Some results are provided along with an analysis for each of three smaller General Electric (GE) Ada development projects that utilized variations on this approach. Finally some considerations are identified for larger scale implementation.

Usavage, Paul, Jr.↗

Data Farming and Defense Applications

.Data farm,ing uses simulation modeling, high performance computing, experimental design and analysis to examine questions of interest with large possibility spaces. This methodology allows for the examination of whole landscapes of potential outcomes and provides the capability of executing enough experiments so that outliers might be captured and examined for insights. It can be used to conduct sensitivity studies, to support validation and verification of models, to iteratively optimize outputs using heuristic search and discovery, and as an aid to decision-makers in understanding complex relationships of factors. In this paper we describe efforts at the Naval Postgraduate School in developing these new and emerging tools. We also discuss data farming in the context of application to questions inherent in military decision-making. The particular application we illustrate here is social network modeling to support the countering of improvised explosive devices.

Horne, Gary↗

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because it can aid in both cybersecurity analysis and the evaluation of other cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

cyber-physical systems↗

A Lagrangian Study of the Transition from Shallow to Deep Convection Using ASR Observations and Les Simulations (Final Report)

With the support from this grant, we have made the following accomplishments. We have found that a formula for fractional entrainment rate, a key aspect for parameterization moist convection, that works for both shallow and deep convection, which provide a promising direction for unified treatment of entrainment for both shallow and deep convection. We also examined the formulation of vertical velocity and showed that the effect of non-hydrostatic pressure and entrainment on vertical velocity are not constants, as assumed in past studies, but can be computed using a simple model for the cloudy updrafts. These results also apply to both deep and shallow convection, which opens the door for a more physically based parameterization of the updraft vertical velocity. We have also conducted extensive analysis of the RACORO aircraft data and have published the results in Wei et al. (2020). We have made extensive effort scrutinizing the data in detail and examining the various hypotheses with the aid of the LES simulations. This was the first application of the modified Paluch diagram on modern aircraft data and the first comprehensive analysis of mixing in clouds using real data (instead of only LES output) in a very long time. These analyses enhanced the science return of the ASR aircraft measurements. This grant also supported a study of the collisions among cold pools and an effort to build parameterizations of moist convection using tools developed in control theory.

42 ENGINEERING↗

Ordering design tasks based on coupling strengths

The design process associated with large engineering systems requires an initial decomposition of the complex system into modules of design tasks which are coupled through the transference of output data. In analyzing or optimizing such a coupled system, it is essential to be able to determine which interactions figure prominently enough to significantly affect the accuracy of the system solution. Many decomposition approaches assume the capability is available to determine what design tasks and interactions exist and what order of execution will be imposed during the analysis process. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature for DeMAID (Design Manager's Aid for Intelligent Decomposition) will allow the design manager to use coupling strength information to find a proper sequence for ordering the design tasks. In addition, these coupling strengths aid in deciding if certain tasks or couplings could be removed (or temporarily suspended) from consideration to achieve computational savings without a significant loss of system accuracy. New rules are presented and two small test cases are used to show the effects of using coupling strengths in this manner.

Rogers, James L., Jr.↗

Ordering Design Tasks Based on Coupling Strengths

The design process associated with large engineering systems requires an initial decomposition of the complex system into modules of design tasks which are coupled through the transference of output data. In analyzing or optimizing such a coupled system, it is essential to be able to determine which interactions figure prominently enough to significantly affect the accuracy of the system solution. Many decomposition approaches assume the capability is available to determine what design tasks and interactions exist and what order of execution will be imposed during the analysis process. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature for DeMAID (Design Manager's Aid for Intelligent Decomposition) will allow the design manager to use coupling strength information to find a proper sequence for ordering the design tasks. In addition, these coupling strengths aid in deciding if certain tasks or couplings could be removed (or temporarily suspended) from consideration to achieve computational savings without a significant loss of system accuracy. New rules are presented and two small test cases are used to show the effects of using coupling strengths in this manner.

Rogers, J. L.↗