Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “integrated modelling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Modeling of integrated sunlight velocity measurements: The effect of surface darkening by magnetic fields

It has been known since the work by Claverie et al. (1982) that integrated-sunlight velocities measured with the resonance scattering technique show variations with time scales of weeks to months. The cause can be understood in terms of the effects of solar activity as was pointed out by Edmunds & Gough (1983) and Andersen & Maltby (1983). The latter authors included a model calculation based on sunspot areas which showed good promise of being able to quantitatively reproduce the observed velocity shifts. We discuss in this paper a new modeling effort based on daily magnetograms obtained at the 150-ft tower on Mt. Wilson. This type of database is more quantitative than sunspot area. Similar maps of magnetically sensitive quantities will be measured on a continuous time base as part of several planned helioseismology experiments (from space with the Solar Oscillations Imagery/Michelson Doppler Imager (SOI/MDI) experiment on the Solar and Heliospheric Observatory (SOHO), see Scherrer et al. (1991) or with ground-based networks, see Hill & Leibacher (1991)). We discuss the correlations between various magnetically sensitive quantities and develop a new model for the effects of magnetic field on line profiles and surface brightness. From these correlations we integrate the line profile changes over the solar surface using observed magnetic field strengths measured at lambda 5250.2. The final output is a new model for the effects of magnetic fields on integrated sunlight velocities which we compare with daily offset velocities derived from the International Research on the Interior of the Sun (IRIS)-T instrument at the Observatorio del Teide.

Ulrich, R. K.↗
DOE OSTI2018

An overview of methods to identify and manage uncertainty for modelling problems in the water-environment-agriculture cross-sector

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclectic treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

A dynamic model for assessing the effects of management strategies on the reduction of construction and demolition waste

Highlights: Black-Right-Pointing-Pointer We proposes a model for projecting C and D waste reduction of construction projects. Black-Right-Pointing-Pointer The model can simulate effects of various management strategies on waste reduction. Black-Right-Pointing-Pointer The model integrates all essential variables that affect C and D waste reduction. Black-Right-Pointing-Pointer By using the model, best strategies could be identified before being implemented. - Abstract: During the past few decades, construction and demolition (C and D) waste has received increasing attention from construction practitioners and researchers worldwide. A plethora of research regarding C and D waste management has been published in various academic journals. However, it has been determined that existing studies with respect to C and D waste reduction are mainly carried out from a static perspective, without considering the dynamic and interdependent nature of the whole waste reduction system. This might lead to misunderstanding about the actual effect of implementing any waste reduction strategies. Therefore, this research proposes a model that can serve as a decision support tool for projecting C and D waste reduction in line with the waste management situation of a given construction project, and more importantly, as a platform for simulating effects of various management strategies on C and D waste reduction. The research is conducted using system dynamics methodology, which is a systematic approach that deals with the complexity - interrelationships and dynamics - of any social, economic and managerial system. The dynamic model integrates major variables that affect C and D waste reduction. In this paper, seven causal loop diagrams that can deepen understanding about the feedback relationships underlying C and D waste reduction system are firstly presented. Then a stock-flow diagram is formulated by using software for system dynamics modeling. Finally, a case study is used to illustrate the validation and application of the proposed model. Results of the case study not only built confidence in the model so that it can be used for quantitative analysis, but also assessed and compared the effect of three designed policy scenarios on C and D waste reduction. One major contribution of this study is the development of a dynamic model for evaluating C and D waste reduction strategies under various scenarios, so that best management strategies could be identified before being implemented in practice.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
DOE OSTI2022

Drivers of Phytoplankton Variability in and Near the Pearl River Estuary, South China Sea During Typhoon Hato (2017): A Numerical Study

The Pearl River estuary-coastal system in the Northern South China Sea is frequently affected by tropical cyclones (TCs) every year. Previous in-situ and remote sensing studies have found typhoons can enhance phytoplankton biomass and induce blooms in this region. However, the mechanistic links between phytoplankton blooms and typhoons have not been well elucidated due to the interplay of multiple processes along the land-ocean-atmosphere interfaces. Unravelling these interactions will have to rely on an integrated modelling system. In this work, we constructed a realistic, 3-dimensional, land-ocean-atmosphere modelling system with the marine ecosystem and sediment components for the China Great Bay Area. By using the integrated modelling system, we quantitatively investigated phytoplankton response to hydrological conditions variations under Typhoon Hato (2017), a strong typhoon case. Passive tracer experiments showed that with high river discharge induced by heavy rainfall, the residence time of Lingding Bay is as short as 15-day, less than half of that under the climatological discharge. The increase in freshwater pulse washed out the phytoplankton biomass within Lingding Bay. While for the offshore region, the source and sink terms analysis showed that the increase of phytoplankton biomass in the first week was because of the uplift of nutrient-rich subsurface water, while in the second week was because of the seaward propagated nearshore high phytoplankton biomass water. While riverine nutrients support phytoplankton growth in the third week, a large part of phytoplankton biomass was lost to zooplankton grazing, showing the system shifted from the bottom-up control to the top-down control.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cyber-Informed Engineering (CIE) Integration into Model- Based Systems Engineering (MBSE)

Engineering design in the field of industrial engineering, such as designing automated factories or warehouses, is critical for the effective operation of facilities. Any design flaws introduced early can result in significant capital expenses to correct. However, early-stage engineering design is inherently complex. The systems are not yet built, requiring designers to integrate various aspects, including digital engineering and cybersecurity, to support virtual representations throughout the design process. In this study, we propose an approach to integrate Cyber-Informed Engineering (CIE) principles into model-based systems engineering (MBSE). This approach facilitates the development of a digital thread for engineering systems, ensuring secure digital artifacts in the design of industrial engineering systems.

42 - ENGINEERING↗
NASA NTRS2009

NASA Tech Briefs, September 2009

opics covered include: Filtering Water by Use of Ultrasonically Vibrated Nanotubes; Computer Code for Nanostructure Simulation; Functionalizing CNTs for Making Epoxy/CNT Composites; Improvements in Production of Single-Walled Carbon Nanotubes; Progress Toward Sequestering Carbon Nanotubes in PmPV; Two-Stage Variable Sample-Rate Conversion System; Estimating Transmitted-Signal Phase Variations for Uplink Array Antennas; Board Saver for Use with Developmental FPGAs; Circuit for Driving Piezoelectric Transducers; Digital Synchronizer without Metastability; Compact, Low-Overhead, MIL-STD-1553B Controller; Parallel-Processing CMOS Circuitry for M-QAM and 8PSK TCM; Differential InP HEMT MMIC Amplifiers Embedded in Waveguides; Improved Aerogel Vacuum Thermal Insulation; Fluoroester Co-Solvents for Low-Temperature Li+ Cells; Using Volcanic Ash to Remove Dissolved Uranium and Lead; High-Efficiency Artificial Photosynthesis Using a Novel Alkaline Membrane Cell; Silicon Wafer-Scale Substrate for Microshutters and Detector Arrays; Micro-Horn Arrays for Ultrasonic Impedance Matching; Improved Controller for a Three-Axis Piezoelectric Stage; Nano-Pervaporation Membrane with Heat Exchanger Generates Medical-Grade Water; Micro-Organ Devices; Nonlinear Thermal Compensators for WGM Resonators; Dynamic Self-Locking of an OEO Containing a VCSEL; Internal Water Vapor Photoacoustic Calibration; Mid-Infrared Reflectance Imaging of Thermal-Barrier Coatings; Improving the Visible and Infrared Contrast Ratio of Microshutter Arrays; Improved Scanners for Microscopic Hyperspectral Imaging; Rate-Compatible LDPC Codes with Linear Minimum Distance; PrimeSupplier Cross-Program Impact Analysis and Supplier Stability Indicator Simulation Model; Integrated Planning for Telepresence With Time Delays; Minimizing Input-to-Output Latency in Virtual Environment; Battery Cell Voltage Sensing and Balancing Using Addressable Transformers; Gaussian and Lognormal Models of Hurricane Gust Factors; Simulation of Attitude and Trajectory Dynamics and Control of Multiple Spacecraft; Integrated Modeling of Spacecraft Touch-and-Go Sampling; Spacecraft Station-Keeping Trajectory and Mission Design Tools; Efficient Model-Based Diagnosis Engine; and DSN Simulator.

Source record↗
DOE OSTI2025

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Modeling for Integrated Science Management and Resilient Systems Development

Many physiological, environmental, and operational risks exist for crewmembers during spaceflight. An understanding of these risks from an integrated perspective is required to provide effective and efficient mitigations during future exploration missions that typically have stringent limitations on resources available, such as mass, power, and crew time. The Human Research Program (HRP) is in the early stages of developing collaborative modeling approaches for the purposes of managing its science portfolio in an integrated manner to support cross-disciplinary risk mitigation strategies and to enable resilient human and engineered systems in the spaceflight environment. In this talk, we will share ideas being explored from fields such as network science, complexity theory, and system-of-systems modeling. Initial work on tools to support these explorations will be discussed briefly, along with ideas for future efforts.

Shelhamer, M.↗
DOE OSTI2013

MODEL BASED BIOMASS SYSTEM DESIGN OF FEEDSTOCK SUPPLY SYSTEMS FOR BIOENERGY PRODUCTION

Engineering feedstock supply systems that deliver affordable, high-quality biomass remains a challenge for the emerging bioenergy industry. Cellulosic biomass is geographically distributed and has diverse physical and chemical properties. Because of this feedstock supply systems that deliver cellulosic biomass resources to biorefineries require integration of a broad set of engineered unit operations. These unit operations include harvest and collection, storage, preprocessing, and transportation processes. Design decisions for each feedstock supply system unit operation impact the engineering design and performance of the other system elements. These interdependencies are further complicated by spatial and temporal variances such as climate conditions and biomass characteristics. This paper develops an integrated model that couples a SQL-based data management engine and systems dynamics models to design and evaluate biomass feedstock supply systems. The integrated model, called the Biomass Logistics Model (BLM), includes a suite of databases that provide 1) engineering performance data for hundreds of equipment systems, 2) spatially explicit labor cost datasets, and 3) local tax and regulation data. The BLM analytic engine is built in the systems dynamics software package PowersimTM. The BLM is designed to work with thermochemical and biochemical based biofuel conversion platforms and accommodates a range of cellulosic biomass types (i.e., herbaceous residues, short- rotation woody and herbaceous energy crops, woody residues, algae, etc.). The BLM simulates the flow of biomass through the entire supply chain, tracking changes in feedstock characteristics (i.e., moisture content, dry matter, ash content, and dry bulk density) as influenced by the various operations in the supply chain. By accounting for all of the equipment that comes into contact with biomass from the point of harvest to the throat of the conversion facility and the change in characteristics, the BLM evaluates economic performance of the engineered system, as well as determining energy consumption and green house gas performance of the design. This paper presents a BLM case study delivering corn stover to produce cellulosic ethanol. The case study utilizes the BLM to model the performance of several feedstock supply system designs. The case study also explores the impact of temporal variations in climate conditions to test the sensitivity of the engineering designs. Results from the case study show that under certain conditions corn stover can be delivered to the cellulosic ethanol biorefinery for $35/dry ton.

09 BIOMASS FUELS↗
DOE OSTI2014

Nonlocal symmetries of the Hirota-Satsuma coupled Korteweg-de Vries system and their applications: Exact interaction solutions and integrable hierarchy

The nonlocal symmetry is derived from the known Darboux transformation (DT) of the Hirota-Satsuma coupled Korteweg-de Vries (HS-cKdV) system, and infinitely many nonlocal symmetries are given by introducing the internal parameters. By extending the HS-cKdV system to an auxiliary system with five dependent variables, the prolongation is found to localize the so-called seed nonlocal symmetry related to the DT. By applying the general Lie point symmetry method to this enlarged system, we obtain two main results: a new type of finite symmetry transformation is derived, which is different from the initial DT and can generate new solutions from old ones; some novel exact interaction solutions among solitons and other complicated waves including periodic cnoidal waves and Painlevé waves are computed through similarity reductions. In addition, two kinds of new integrable models are proposed from the obtained nonlocal symmetry: the negative HS-cKdV hierarchy by introducing the internal parameters; the integrable models both in lower and higher dimensions by restricting the symmetry constraints.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

AI/OR computational model for integrating qualitative and quantitative design methods

A theoretical framework for integrating qualitative and numerical computational methods for optimally-directed design is described. The theory is presented as a computational model and features of implementations are summarized where appropriate. To demonstrate the versatility of the methodology we focus on four seemingly disparate aspects of the design process and their interaction: (1) conceptual design, (2) qualitative optimal design, (3) design innovation, and (4) numerical global optimization.

Agogino, Alice M.↗
NASA NTRS2004

Using CMMI for Improvement at GSFC

This viewgraph presentation discusses the Capability Maturity Model Integrated (CMMI) is an integrated framework for maturity models and associated products that integrates the two key disciplines that are inseparable in a systems development activity: software engineering and systems engineering.

Godfrey, Sara H.↗
DOE OSTI2024

Infinite Family of Integrable Sigma Models Using Auxiliary Fields

We introduce a class of 2D sigma models which are parametrized by a function of one variable. In addition to the physical field g , these models include an auxiliary field v α which mediates interactions in a prescribed way. We prove that every theory in this family is classically integrable, in that it possesses an infinite set of conserved charges in involution, which can be constructed from a Lax representation for the equations of motion. This class includes the principal chiral model (PCM) and all deformations of the PCM by functions of the energy-momentum tensor. Published by the American Physical Society 2024

Physics↗
DOE OSTI2017

Development of Computational Tools for Modeling Thermal and Radiation Effects on Grain Boundary Segregation and Precipitation in Fe-Cr-Ni-based Alloys

This work aims at developing computational tools for modeling thermal and radiation effects on solute segregation at grain boundaries (GBs) and precipitation. This report described two major efforts. One is the development of computational tools on integrated modeling of thermal equilibrium segregation (TES) and radiation-induced segregation (RIS), from which synergistic effects of thermal and radiation, pre-existing GB segregation have been taken into consideration. This integrated modeling was used in describing the Cr and Ni segregation in the Fe-Cr-Ni alloys. The other effort is thermodynamic modeling on the Fe-Cr-Ni-Mo system which includes the major alloying elements in the investigated alloys in the Advanced Radiation Resistant Materials (ARRM) program. Through thermodynamic calculation, we provide baseline thermodynamic stability of the hardening phase Ni2(Cr,Mo) in selected Ni-based super alloys, and contribute knowledge on mechanistic understanding on the formation of Ni2(Cr,Mo) in the irradiated materials. The major outcomes from this work are listed in the following: 1) Under the simultaneous thermal and irradiation conditions, radiation-induced segregation played a dominant role in the GB segregation. The pre-existing GB segregation only affects the subsequent radiation-induced segregation in the short time. For the same element, the segregation tendency of Cr and Ni due to TES is opposite to it from RIS. The opposite tendency can lead to the formation of W-shape profile. These findings are consistent with literature observation of the transitory W-shape profile. 2) While TES only affects the distance of one or two atomic layers from GBs, the RIS can affect a broader distance from GB. Therefore, the W-shape due to pre-existing GB segregation is much narrower than that due to composition gradient formed during the transient state. Considering the measurement resolution of Auger or STEM analysis, the segregation tendency due to RIS should play a dominant role in the measured values. However, The GB segregation due to pre-existing GB segregation may affect the chemical potential of element at GB, and subsequently the corrosion resistance. 3) Based on the newly developed thermodynamic database of Fe-Cr-Ni-Mo, we predicted the Ni2(Cr,Mo) as a thermodynamically stable phase in all investigated low Fe-content Ni-based alloys. The calculated phase amount decreases with the increasing Fe content, being consistent with that observed in the irradiated materials. 4) The formation of the Ni2(Cr,Mo) phase in irradiated materials is due to irradiation enhanced diffusion. The calculated equilibrium Ni2(Cr,Mo) amount is more than that observed in the irradiated materials, suggesting that the amount of Ni2(Cr,Mo) is likely to increase more with further irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An Interface Debonding Model for Integrity Assessment of Nuclear Fuel Rods

The integrity degradation of nuclear fuel rods due to material embrittlement resulting from hydride formation has been extensively investigated. Finite element based fracture mechanics models have been proposed to assess the reduction of load capacity of nuclear fuel rod structures with several distribution scenarios of hydrides. In these finite element models, individual hydrides are modeled by opened cracks distributed in bulk matrix. These models are indeed valid for cases where hydrides fractures occur at low load levels. It is important for finite element models to take into account the cases where hydride fractures occur at high load levels, at which bulk matrix material may undergo reasonable high stress or yield. This requires hydride/bulk matrix interface models that can accommodate both bonded and debonded (fractured or crack initiation) behaviors of hydride/matrix interfaces. However, direct modeling debonding behaviors between hydride and bulk matrix is a great challenge. This is because for ductile structural failure simulations ligaments of bulk matrix often undergo large plastic deformation. Complete solutions often unavailable for crack initiation or debonding in media with finite plastic strain using popular implicit finite element technologies. This paper proposes a new computational framework based on discontinuous Galerkin (DG) finite element formulations for easily handling hydride/matrix interface debonding. We present structural failure simulation results for a quarter plane strain rod model with zircaloy materials. It is concluded that the proposed DG interface debonding model is powerful in simulating structural failure due to hydride failure in bulk media with finite plastic deformation. (author)

36 MATERIALS SCIENCE↗
DOE OSTI2017

Dynamic reduced-order models of integrated physics-specific systems for carbon sequestration

In this study, CO 2 leakage from a deep storage reservoir into a shallow groundwater aquifer through a wellbore is simulated using physics-specific models conceptualized as nonisothermal two-phase flow in a deep storage reservoir and through the wellbore, and reactive transport in the aquifer. Supercritical CO 2 is injected into the reservoir subsystem with uncertain permeabilities of reservoir and injection strategies (rate and duration as decision variables). The simulated pressure and CO 2 saturation at an uncertain location are connected to the wellbore model as a boundary condition to output CO 2 flux to the reactive transport model in the shallow aquifer. Uncertainties are propagated from the deep reservoir model, to the wellbore leakage model, and eventually to the reactive transport model, thus contributing to system performance. Finally, to minimize the risk associated with the CO 2 leakage, we develop dynamic reduced order models for quantifying and managing the uncertainty propagation.

58 GEOSCIENCES↗