Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Model based development”

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 181 records · Page 10

Development of Predictive Model for Accurate Rupture Time from Multi-Axial Creep in Alloy 709 with Physics-Based Simulations

A physics-based model is developed to predict multiaxial creep behavior in Alloy 709 (A709), an advanced austenitic stainless steel intended for high-temperature applications such as Sodium Fast Reactors (SFRs). Compared to conventional stainless steels like 316H, A709 offers superior high-temperature performance; however, comprehensive data on its multiaxial creep response remain limited. To address this gap, a crystal plasticity finite element (CPFE) framework is used to simulate the deformation and failure mechanisms of A709 under multiaxial loading conditions. The model incorporates an extended Hu-Cocks dislocation creep formulation that accounts for precipitation effects, along with the Sham–Needleman model to capture grain boundary cavitation-driven failure. These advanced constitutive models enable a detailed understanding of the interplay between microstructural evolution and macroscopic creep response. Furthermore, the study evaluates the predictive accuracy of various effective stress measures in estimating creep rupture life, leveraging simulated multiaxial creep data. The findings provide critical insights into the applicability of different stress measures for engineering design and life prediction of A709 components operating under complex loading conditions. This work contributes to improving the reliability of high-temperature structural components by advancing predictive modeling capabilities for advanced austenitic steels.

Alloy 709↗

History Matching and Prediction of a Polymer Flood Pilot in Heavy Oil Reservoir on Alaska North Slope

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope is ongoing. After more than 3 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is less than that of the same polymer used in a polymer pilot in Argentina.

Wang, Xindan↗

Development of an empirically based dynamic biomechanical strength model

The focus here is on the development of a dynamic strength model for humans. Our model is based on empirical data. The shoulder, elbow, and wrist joints are characterized in terms of maximum isolated torque, position, and velocity in all rotational planes. This information is reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining the torque as a function of position and velocity. The isolated joint torque equations are then used to compute forces resulting from a composite motion, which in this case is a ratchet wrench push and pull operation. What is presented here is a comparison of the computed or predicted results of the model with the actual measured values for the composite motion.

Pandya, A.↗

Quality control for community-based sea-ice model development

A new collaborative organization for sea-ice model development, the CICE Consortium, has devised quality control procedures to maintain the integrity of its numerical codes' physical representations, enabling broad participation from the scientific community in the Consortium's open software development environment. Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, we formulate quality control methods that exploit common statistical properties of sea-ice thickness, and test for significant changes in model results in a computationally efficient manner. New additions and changes to CICE are graded into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. These modifications are assessed using criteria that account for the high level of autocorrelation in sea-ice time series, along with a quadratic skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations. These metrics also provide objective guidance for assessing new physical representations and code functionality.

58 GEOSCIENCES↗

Developments in Physics-Based Modeling and Machine Learning for Environmental Effects in Nuclear Materials [Slides]

This presentation is part of an annual review for the new Advanced Materials and Manufacturing Technologies program under the Office of Nuclear Energy within the Department of Energy. This presentation covers advances in physics-based modeling and machine learning for environmental effects in nuclear materials. It discusses efforts in combining density functional theory with machine learning to predict material properties, studying irradiation defect recombination, and improving MOOSE-based tools for crystal plasticity modeling and the Stochastic Tools Module.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Flex Fuel Optimized SI and HCCI Engine

The central objective of the proposed work is to demonstrate an HCCI (homogeneous charge compression ignition) capable SI (spark ignited) engine that is capable of fast and smooth mode transition between SI and HCCI combustion modes. The model-based control technique was used to develop and validate the proposed control strategy for the fast and smooth combustion mode transition based upon the developed control-oriented engine; and an HCCI capable SI engine was designed and constructed using production ready two-step valve-train with electrical variable valve timing actuating system. Finally, smooth combustion mode transition was demonstrated on a metal engine within eight engine cycles. The Chrysler turbocharged 2.0L I4 direct injection engine was selected as the base engine for the project and the engine was modified to fit the two-step valve with electrical variable valve timing actuating system. To develop the model-based control strategy for stable HCCI combustion and smooth combustion mode transition between SI and HCCI combustion, a control-oriented real-time engine model was developed and implemented into the MSU HIL (hardware-in-the-loop) simulation environment. The developed model was used to study the engine actuating system requirement for the smooth and fast combustion mode transition and to develop the proposed mode transition control strategy. Finally, a single cylinder optical engine was designed and fabricated for studying the HCCI combustion characteristics. Optical engine combustion tests were conducted in both SI and HCCI combustion modes and the test results were used to calibrate the developed control-oriented engine model. Intensive GT-Power simulations were conducted to determine the optimal valve lift (high and low) and the cam phasing range. Delphi was selected to be the supplier for the two-step valve-train and Denso to be the electrical variable valve timing system supplier. A test bench was constructed to develop control strategies for the electrical variable valve timing (VVT) actuating system and satisfactory electrical VVT responses were obtained. Target engine control system was designed and fabricated at MSU for both single-cylinder optical and multi-cylinder metal engines. Finally, the developed control-oriented engine model was successfully implemented into the HIL simulation environment. The Chrysler 2.0L I4 DI engine was modified to fit the two-step vale with electrical variable valve timing actuating system. A used prototype engine was used as the base engine and the cylinder head was modified for the two-step valve with electrical VVT actuating system. Engine validation tests indicated that cylinder #3 has very high blow-by and it cannot be reduced with new pistons and rings. Due to the time constraint, it was decided to convert the four-cylinder engine into a single cylinder engine by blocking both intake and exhaust ports of the unused cylinders. The model-based combustion mode transition control algorithm was developed in the MSU HIL simulation environment and the Simulink based control strategy was implemented into the target engine controller. With both single-cylinder metal engine and control strategy ready, stable HCCI combustion was achived with COV of 2.1% Motoring tests were conducted to validate the actuator transient operations including valve lift, electrical variable valve timing, electronic throttle, multiple spark and injection controls. After the actuator operations were confirmed, 15-cycle smooth combustion mode transition from SI to HCCI combustion was achieved; and fast 8-cycle smooth combustion mode transition followed. With a fast electrical variable valve timing actuator, the number of engine cycles required for mode transition can be reduced down to five. It was also found that the combustion mode transition is sensitive to the charge air and engine coolant temperatures and regulating the corresponding temperatures to the target levels during the combustion mode transition is the key for a smooth combustion mode transition. As a summary, the proposed combustion mode transition strategy using the hybrid combustion mode that starts with the SI combustion and ends with the HCCI combustion was experimentally validated on a metal engine. The proposed model-based control approach made it possible to complete the SI-HCCI combustion mode transition within eight engine cycles utilizing the well controlled hybrid combustion mode. Without intensive control-oriented engine modeling and HIL simulation study of using the hybrid combustion mode during the mode transition, it would be impossible to validate the proposed combustion mode transition strategy in a very short period.

33 ADVANCED PROPULSION SYSTEMS↗

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

Hall, Gardiner A.↗

Development of a Mechanistic-Based Healing Model for Self-Healing Glass Seals

Self-healing glass, a recent development of hermetic sealant materials, has the ability to effectively repair damage when heated to elevated temperatures; thus, able to extend its service life. Since crack healing morphological changes in the glass material are usually temperature and stress dependent, quantitative studies to determine the effects of thermo-mechanical conditions on the healing behavior of the self-healing glass sealants are extremely useful to accommodate the design and optimization of the sealing systems within SOFCs. The goal of this task is to develop a mechanistic-based healing model to quantify the stress and temperature dependent healing behavior. A two-step healing mechanism was developed and implemented into finite element (FE) models through user-subroutines. Integrated experimental/kinetic Monte Carlo (kMC) simulation methodology was taken to calibrate the model parameters. The crack healing model is able to investigate the effects of various thermo-mechanical factors; therefore, able to determine the critical conditions under which the healing mechanism will be activated. Furthermore, the predicted results can be used to formulate the continuum damage-healing model and to assist the SOFC stack level simulations in predicting and evaluating the effectiveness and the performance of various engineering seal designs.

Fuel Cell↗

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups.

59 BASIC BIOLOGICAL SCIENCES↗

Unifying Model-Based and Reactive Programming within a Model-Based Executive

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

Williams, Brian C.↗

On formulations for modeling pressurized cracks within phase-field methods for fracture

Over the past few decades, the phase-field method for fracture has seen widespread appeal due to the many benefits associated with its ability to regularize a sharp crack geometry. Along the way, several different models for including the effects of pressure loads on the crack faces have been developed. Further, this work investigates the performance of these models and compares them to a relatively new formulation for incorporating crack-face pressure loads. It is shown how the new formulation can be obtained either by modifying the trial space in the traditional variational principle or by postulating a new functional that is dependent on the rates of the primary variables. The key differences between the new formulation and existing models for pressurized cracks in a phase-field setting are highlighted. Model-based simulations developed with discretized versions of the new formulation and existing models are then used to illustrate the advantages and differences. In order to analyze the results, a domain form of the J-integral is developed for diffuse cracks subjected to pressure loads. Results are presented for a one-dimensional cohesive crack, steady crack growth, and crack nucleation from a pressurized enclosure.

42 ENGINEERING↗

Dislocation vs. production bias revisited with account of radiation-induced emission bias I. Void swelling under electron and light ion irradiation

Early experimental data on void swelling in electron-irradiated materials disagree with the dislocation bias models based on the dislocation-point defect elastic interactions. Later this became one of the reasons that prompted the development of models based on production bias (PBM) as the main driver for swelling, which assumed that the dislocation bias was much lower than that predicted by theory. However, the PBM in its present form fails to account for important and common observations: the indefinite void growth often observed under cascade irradiation and the swelling saturation observed under high dose irradiation and in void lattices. In this paper we show that these contradictions can be naturally resolved in the framework of the rate theory modified with account of the radiation-induced vacancy emission from extended defects, such as voids, dislocations and grain boundaries. The modified rate theory agrees well with the experimental data, which proves that original dislocation bias should be used in rate theory models in different irradiation. The modified theory predictions include (but not limited to) the radiation-induced annealing of voids, swelling saturation under high dose irradiation, generally, and in void lattices, in particular.

Dubinko, Volodymyr↗

A techno-economic assessment of membrane distillation for treatment of Marcellus shale produced water

Membrane distillation (MD) is a promising desalination technology for treatment of high salinity shale gas produced water. Techno-economic assessment (TEA) is necessary for evaluating the economic feasibility of MD for produced water treatment as compared to other shale gas produced water management strategies. A detailed TEA for a hypothetical 0.5 million gallons per day (MGD) direct contact MD (DCMD) that concentrates produced water from 10% (100,000 mg/L) Total Dissolved Solids (TDS) to 30% salinity is presented in this study. The model is developed based on a combination of experimental results, ASPEN Plus process model, best available engineering knowledge, and cost estimates. Analysis reveals that thermal energy cost for MD operation contributes the most to total cost of treating produced water in an MD plant. Additionally, the results of sensitivity analysis reveal that feed TDS level and thermal energy price have a significant impact on total cost of treating produced water. We also explore the implications of utilizing waste heat on the economics of the MD technology for produced water treatment. Here the results reveal that the total cost of treating produced water using MD is $\$$5.70/m 3 feed which decreases significantly to $\$$0.74/m 3 feed when MD is integrated with a source of waste heat.

42 ENGINEERING↗

South-North and radial traverses through the interplanetary dust cloud

Identical in situ dust detectors are flown on board the Galileo and Ulysses spacecraft. They record impacts of micrometeoroids in the ecliptic plane at heliocentric distances from 0.7 to 5.4 AU and in a plane almost perpendicular to the ecliptic from -79 deg to +79 deg ecliptic latitude. The combination of both Ulysses and Galileo measurements yield information about the radial and latitudinal distributions of micron and sub-micron sized dust in the solar system. Two types of dust particles were found to dominate the dust flux in interplanetary space: (1) Interplanetary micrometeoroids covering a wide mass range from 10(exp -16) to 10(exp -6) gr are mostly recorded inside 3 AU, and at latitudes below 30 deg; and (2) Interstellar grains with masses between 10(exp -14) and 10(exp -12) gr have been positively identified outside 3 AU near the ecliptic plane and outside 1.8 AU at high ecliptic latitudes (> 50 deg). Interstellar grains move on hyperbolic trajectories through the planetary system and constitute the dominant dust flux (1.5 x 10(exp -4)/ sq m sec) in the outer solar system and at high ecliptic latitudes. In order to compare and analyze the Galileo and Ulysses data sets, a new model is developed based on Divine's (1993) "Five populations of interplanetary meteoroids" model. By using this model, which takes into account the measured velocities and the effect of radiation pressure on small particles, we define four populations of meteoroids on elliptical orbits plus one population on hyperbolic orbits that all can fit the micrometeoroid flux observed by Galileo and Ulysses.

Gruen, E.↗

Ultrafast High Accuracy PCRTM_SOLAR Model for Cloudy Atmosphere

An ultrafast high accuracy PCRTM_SOLAR model is developed based on PCA compression and principal component-based radiative transfer model (PCRTM). A fast algorithm for simulation of multi-scattering properties of cloud and/or aerosols is integrated into the fast infrared PCRTM. We completed radiance simulation and training for instruments, such as IASI, AIRS, CrIS, NASTI and SHIS, under diverse conditions. The new model is 5 orders faster than 52-stream DISORT with very high accuracy for cloudy sky radiative transfer simulation. It is suitable for hyperspectral remote data assimilation and cloudy sky retrievals.

Yang, Qiguang↗

Impact of Blockchain Delay on Grid-Tied Solar Inverter Performance: Preprint

This paper investigates the impact of the delay resulting from a blockchain, a promising security measure, for a hierarchical control system of inverters connected to the grid. The blockchain communication network is designed at the secondary control layer for resilience against cyberattacks. To represent the latency in the communication channel, a model is developed based on the complexity of the blockchain framework. Taking this model into account, this work evaluates the plant’s performance subject to communication delays, introduced by the blockchain, among the hierarchical control agents. In addition, this article considers an optimal model-based control strategy that performs the system’s internal control loop. The work shows that the blockchain’s delay size influences the convergence of the power supplied by the inverter to the reference at the point of common coupling. In the results section, real-time simulations on OPAL-RT are performed to test the resilience of two parallel inverters with increasing blockchain complexity.

41 EE - Solar Energy Technologies Office (EE-4S)↗