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At least 379 records · Page 21

The Aerosol-Monsoon Climate System of Asia

In Asian monsoon countries such as China and India, human health and safety problems caused by air-pollution are worsening due to the increased loading of atmospheric pollutants stemming from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash flood or prolonged drought, has caused major loss of human lives, and damages in crop and properties with devastating societal impacts on Asian countries. Historically, air-pollution and monsoon research are treated as separate problems. However a growing number of recent studies have suggested that the two problems may be intrinsically intertwined and need to be studied jointly. Because of complexity of the dynamics of the monsoon systems, aerosol impacts on monsoons and vice versa must be studied and understood in the context of aerosol forcing in relationship to changes in fundamental driving forces of the monsoon climate system (e.g. sea surface temperature, land-sea contrast etc.) on time scales from intraseasonal variability (~weeks) to climate change (~ multi-decades). Indeed, because of the large contributions of aerosols to the global and regional energy balance of the atmosphere and earth surface, and possible effects of the microphysics of clouds and precipitation, a better understanding of the response to climate change in Asian monsoon regions requires that aerosols be considered as an integral component of a fully coupled aerosol-monsoon system on all time scales. In this paper, using observations and results from climate modeling, we will discuss the coherent variability of the coupled aerosol-monsoon climate system in South Asia and East Asia, including aerosol distribution and types, with respect to rainfall, moisture, winds, land-sea thermal contrast, heat sources and sink distributions in the atmosphere in seasonal, interannual to climate change time scales. We will show examples of how elevated absorbing aerosols (dust and black carbon) may interact with monsoon dynamics to produce feedback effects on the atmospheric water cycle, leading to in accelerated melting of snowpacks over the Himalayas and Tibetan Plateau, and subsequent changes in evolution of the pre-monsoon and peak monsoon rainfall, moisture and wind distributions in South Asia and East Asia.

Lau, William K. M.↗

Extended Low Load Boiler Operation to Improve Performance and Economics of an Existing Coal Fired Power Plant (Final Report)

The overall goal is to improve the performance and economics of existing coal fired power plants by extending low load boiler operation to lower loads than is currently achievable. The objective of this program is to develop and validate sensor hardware and analytical algorithms to lower plant operating expenses (OPEX) for the currently operating pulverized coal utility boiler fleet. Coal fired utility boilers are increasingly under grid dispatch pressure. In some cases, the coal fired cost of generation is noncompetitive with respect to natural gas generation and subsidized renewable sources. To remain profitable and remain fully compliant with existing environmental regulations, the installed coal fired fleet must find technologies which allow it to move into a more flexible cyclic load dispatch model. Today the installed coal fired utility fleet must be cost of generation competitive, fully emissions compliant, and responsive to the variability inherent in renewable energy generation sources. In the Phase I of the project, GE Steam Power, Inc. (GE) performed modeling of different operating scenarios for low load operation using an existing full plant dynamic model developed for a 660MW steam power plant. Sensors and analytic algorithms to enable a stable and steady coal supply for low load pulverizer operation were identified and tested at the Pulverizer Development Facility (PDF) at GE’s Clean Energy Center in Bloomfield, Connecticut. Sensors and analytic algorithms to enable stable combustion for low load operation were identified and tested at the 15 MWth Industrial Scale Burner facility (ISBF) at GE’s Clean Energy Center. A concept was developed to test the sensors and control algorithms, down selected after testing, at a full-scale coal fired power plant. A budget estimate was then developed, and the concept was implemented at an existing utility power plant. The specific objectives of the experimental work were to: • Identify and select sensors and analytic algorithms for monitoring coal pulverizer operation at lower loads to provide stable operation and appropriate coal fineness at lower coal throughput; Identify and select sensors and analytic algorithms for a Boiler Flame Stability Monitor to better balance air and fuel at each burner. This enables a reduction in a coal boiler’s safe low load power level while maintaining stable flame characteristics; Develop a concept in Phase I for low load operation of a full-scale power plant and develop a budget estimate for testing and execute the test plan at an existing plant in Phase II; Validate the capability of the extended low load boiler system to extend the minimum load operating point in a safe and reliable manner on an existing full-scale utility boiler. At the completion of this experimental study, GE has developed a set of sensors and analytic algorithms, down selected after testing, that have the potential to enable safe low load operation of a utility boiler. GE has also identified a host site for testing these identified sensors and analytic algorithms. GE has generated a full set of deliverables that provide sufficient information to proceed with the next step of testing at a host site. This includes a potential host site and budget estimate for concept testing at host site. In the Phase II of the project, a series of field tests were completed to validate the extended low load boiler operation, which consisted of detailed engineering, installation, commissioning, and testing the additional sensors and analytics for the coal-fired combustion system on an existing full-scale utility boiler. The optimization work has been supported by the host plant and endorsed by their engineering and operation staff.

01 COAL, LIGNITE, AND PEAT↗

Development of a Rotor-Body Coupled Analysis for an Active Mount Aeroelastic Rotor Testbed

At the Langley Research Center an active mount rotorcraft testbed is being developed for use in the Langley Transonic Dynamics Tunnel. This testbed, the second generation version of the Aeroelastic Rotor Experimental System (ARES-II), can impose rotor hub motions and measure the response so that rotor-body coupling phenomena may be investigated. An analytical method for coupling an aeroelastically scaled model rotor system to the ARES-II is developed in the current study. Models of the testbed and the rotor system are developed in independent analyses, and an impedance-matching approach is used to couple the rotor system to the testbed. The development of the analytical models and the coupling method is examined, and individual and coupled results are presented for the testbed and rotor system. Coupled results are presented with and without applied hub motion, and system loads and displacements are examined. The results show that a closed-loop control system is necessary to achieve desired hub motions, that proper modeling requires including the loads at the rotor hub and rotor control system, and that the strain-gauge balance placed in the rotating system of the ARES-II provided the best loads results.

Wilbur, Matthew L.↗

A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings

Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Investigation of Seal-to-Floor Effects on Semi-Span Transonic Models

In an effort to achieve the maximum possible Reynolds number (Re) when conducting production testing for flight loads aerodynamic databases, it has been the preferred practice of The Boeing Company / Commercial Airplanes (BCA) -- Loads and Dynamics Group since the early 1990's to test large scale semi-span models in the 11- By 11-Foot Transonic Wind Tunnel (TWT) leg of the Unitary Plan Wind Tunnel (UPWT) at the NASA Ames Research Center (ARC). There are many problems related to testing large scale semi-span models of high aspect ratio flexible transport wings, such as; floor boundary layer effects, wing spanwise wall effects, solid blockage buoyancy effects, floor mechanical interference effects, airflow under the model effects, or tunnel flow gradient effects. For most of these issues, BCA has developed and implemented either standard testing methods or numerical correction schemes and these will not be discussed in this document. Other researchers have reported on semi-span transonic testing correction issues, however most of the reported research has been for low Mach testing. Some of the reports for low Mach testing address the difficult problem of preventing undesirable airflow under a semi-span model while ensuring unrestricted main balance functionality, however, for transonic models this issue has gone unresolved. BCA has been cognizant for sometime that there are marked differences in wing pressure distributions from semi-span transonic model testing than from full model or flight testing. It has been suspected that these differences are at least in part due to airflow under the model. Previous efforts by BCA to address this issue have proven to be ineffective or inconclusive and in one situation resulted in broken hardware. This paper reports on a Boeing-NASA collaborative investigation based on a series of small tests conducted between June 2006 and November 2007 in the 11 by 11 foot Transonic Wind Tunnel at NASA Ames on three large commercial jet transport configurations to assess the effects of sealing a semi-span model to the floor and to investigate efficient sealing and testing techniques. This document will show how sealing the model to the floor has a small but remarkably far reaching spanwise effect on wing pressures, wing local section forces and wing force summations.

Sleppy, Mark A.↗

Deployment Potential of Concentrating Solar Power Technologies in California

As states within the United States respond to future grid development goals, there is a growing demand for reliable and resilient nighttime generation that can be addressed by low-cost, long-duration energy storage solutions. This report studies the potential of including concentrating solar power (CSP) in the technology mix to support California’s goals as defined in Senate Bill 100. A joint agency report study that determined potential pathways to achieve the renewable portfolio standard set by the bill did not include CSP, and our work provides information that could be used as a follow-up. This study uses a capacity expansion model configured to have nodal spatial fidelity in California and balancing-area fidelity in the Western Interconnection outside of California. The authors discovered that by applying current technology cost projections CSP fulfills nearly 15% of the annual load while representing just 6% of total installed capacity in 2045, replacing approximately 30 GWe of wind, solar PV, and standalone batteries compared to a scenario without CSP included. The deployment of CSP in the results is sensitive to the technology’s cost, which highlights the importance of meeting cost targets in 2030 and beyond to enable the technology’s potential contribution to California’s carbon reduction goals.

14 SOLAR ENERGY↗

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

A Simulation Framework for Analyzing the Impact of Stochastic Occupant Behaviors on Demand Flexibility in Typical Commercial Buildings

As one of the primary users of the electric grid, buildings and building equipment, including heating, ventilation, and air conditioning (HVAC) systems, can be leveraged to provide the flexible demand needed to balance the grid. Typical strategies to achieve demand flexibility are to reduce electricity use during peak or critical periods by shutting down equipment or relaxing system setpoints, which will inevitably impact the occupants’ comfort. When occupants feel uncomfortable, they may take actions to regain their comfort, and some of those actions (such as turning on a personal fan) may have a negative impact on meeting the demand response goal. Therefore, it is important to incorporate occupant behaviors into the assessment ofthe building demand flexibility potential. In this study, a simulation framework that includes simulation of zone thermal loads, an HVAC system, and occupant behaviors, was developed to investigate the impact of occupant behaviors on demand flexibility. A case study was conducted using a small office model from the U.S. Department of Energy (DOE) Commercial Prototype Building Models to simulate the building envelope and zone loads. An agent-based occupant thermal behavior model was adapted to forecast occupants’ thermal comfort and their resulting thermal behaviors. An artificial neural network (ANN) based airflow model trained from a computational fluid dynamics (CFD) model of the zone was adopted to better predict the ambient environment of each occupant. An air-source heat pump simulation model that was calibrated from a real two-stage air-source heat pump system was used as the HVAC system. A typical load shedding event during peak hours was studied. Repeated simulations were conducted to capture the stochastic effects of occupant behaviors. The interplay between the demand flexibility, occupant comfort and behavior were analyzed by evaluating key performance indicators, including the energy use, occupant discomfort duration, and occupant behavior duration during the peak period. The results suggest that this framework can be used to analyze typical commercial buildings and their HVAC systems in terms ofdemand flexibility potential under the impact of occupant behaviors.

Chen, Zhelun↗

Advanced CO 2 Capture Solvent Systems for Dynamic Power Generation

RTI International, in collaboration with Pacific Northwest National Laboratory (PNNL), Carbon Capture Simulation for Industry Impact (CCSI 2 ), Electricity Power Research Institute (EPRI), and West Virginia University (WVU), successfully completed a joint research effort in developing a cost-effective, resilient, load-following advanced CO 2 capture technology for natural gas power plants. The project’s objective was to develop a CO 2 capture process that maximizes the net present value (NPV) of the electricity sale by minimizing the levelized cost of electricity (LCOE) under dynamic plant loads and high renewable penetration environments. The two key innovations developed in this project were the use of (i) advanced water-lean solvents (WLSs) and (ii) process intensification equipment, such as a rotating packed bed (RPB) absorber and dual-stage flash regeneration. The process’s low CO 2 capture cost is realized through WLSs’ low energy required for solvent regeneration, which lowers the operating cost while RPBs intensify the absorption process and reduces the power plant capital cost. A suite of advanced computational and simulation packages was implemented to guide the process design, validate the dynamic response of the capture plant, evaluate system-wide performance, and maximize the power plant’s profit. The project also engaged with power producers and other stakeholders to ensure its technical relevance and techno-economic viability. The development of this highly disruptive CO 2 capture technology could accelerate the industry adoption and thereby lower the greenhouse gas emissions of the U.S. power sector. Deployment of this technology can increase the reliability and decrease the cost of electricity generation in the U.S. by enabling the use of low-carbon fossil fuels to balance fluctuations of renewable energy availability.

03 NATURAL GAS↗

Research on Earth's rotation and the effect of atmospheric pressure on vertical deformation and sea level variability

The work done under NASA grant NAG5-485 included modelling the deformation of the earth caused by variations in atmospheric pressure. The amount of deformation near coasts is sensitive to the nature of the oceanic response to the pressure. The PSMSL (Permanent Service for Mean Sea Level) data suggest the response is inverted barometer at periods greater than a couple months. Green's functions were constructed to describe the perturbation of the geoid caused by atmospheric and oceanic loading and by the accompanying load-induced deformation. It was found that perturbation of up to 2 cm are possible. Ice mass balance data was used for continental glaciers to look at the glacial contributions to time-dependent changes in polar motion, the lod, the earth's gravitational field, the position of the earth's center-of-mass, and global sea level. It was found that there can be lateral, non-hydrostatic structure inside the fluid core caused by gravitational forcing from the mantle, from the inner core, or from topography at the core/mantle or inner core/outer core boundaries. The nutational and tidal response of a non-hydrostatic earth with a solid inner core was modeled. Monthly, global tide gauge data from PSMSL was used to look at the 18.6-year ocean tide, the 14-month pole tide, the oceanic response to pressure, the linear trend and inter-annual variability in the earth's gravity field, the global sea level rise, and the effects of post glacial rebound. The effects of mantle anelasticity on nutations, earth tides, and tidal variation in the lod was modeled. Results of this model can be used with Crustal Dynamics observations to look at the anelastic dissipation and dispersion at tidal periods. The effects of surface topography on various components of crustal deformation was also modeled, and numerical models were developed of post glacial rebound.

Wahr, John↗

Static and dynamic force/moment measurements in the Eidetics water tunnel

Water tunnels have been utilized in one form or another to explore fluid mechanics and aerodynamics phenomena since the days of Leonardo da Vinci. Water tunnel testing is attractive because of the relatively low cost and quick turn-around time to perform flow visualization experiments and evaluate the results. The principal limitation of a water tunnel is that the low flow speed, which provides for detailed visualization, also results in very small hydrodynamic (aerodynamic) forces on the model, which, in the past, have proven to be difficult to measure accurately. However, the advent of semi-conductor strain gage technology and devices associated with data acquisition such as low-noise amplifiers, electronic filters, and digital recording have made accurate measurements of very low strain levels feasible. The principal objective of this research effort was to develop a multi-component strain gage balance to measure forces and moments on models tested in flow visualization water tunnels. A balance was designed that allows measuring normal and side forces, and pitching, yawing and rolling moments (no axial force). The balance mounts internally in the model and is used in a manner typical of wind tunnel balances. The key differences between a water tunnel balance and a wind tunnel balance are the requirement for very high sensitivity since the loads are very low (typical normal force is 0.2 lbs), the need for water proofing the gage elements, and the small size required to fit into typical water tunnel models.

Carlos J Suarez↗

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

Countermeasures for Mitigation of Sensorimotor Decrements Following Head-Down Bed Rest

BACKGROUND Decrements in functional performance of tasks requiring postural and locomotor control remain common among crewmembers returning to Earth after6months on the International Space Station (ISS). These impairments will presumably be exacerbated after longer exploration-class missions with fewer exercise hardware options. Our recent studies suggest that an in-flight proprioceptive countermeasure may keep the proprioceptive system tuned to respond to upright balance challenges in a gravitational environment. Before testing a proprioceptive countermeasure in-flight, we must conduct an initial proof-of-concept study to determine its potential efficacy in a controlled unloading analog setting. OBJECTIVES We will determine if proprioceptive training during 60 days of 6° head down bed rest (HDBR) mitigates declines in functional task performance. We consider it critical to characterize the interaction between proprioceptive training and exercise. Thus, we will compare 3groupsof subjects(N=12 each): a proprioceptive training group, an exercise plus proprioceptive training group, and a control group(i.e. no training or exercise).The primary outcome measure will be the well-established and operationally relevant seat egress and walk test (also referred to as the functional mobility test)performed before and after HDBR. Other functional tests will also represent high priority exploration mission tasks that require high demand for dynamic control of postural stability. Additional measures will be used to identify the key physiological factors contributing to countermeasure benefits. COUNTERMEASURE METHODS We will use a ground version of our countermeasure to test the efficacy of proprioceptive training while maintaining HDBR constraints. Subjects will remain in the horizontal supine position on a sled that moves freely on air-bearings, similar to a puck on an air hockey table. Subjects will be loaded axially up to one full body weight via lateral cable pulleys towards their feet on an instrumented tilt board using a harness and weights system. Visual feedback of board tilt will be used to guide subjects while they make active tilts. Exercise and proprioceptive training prescriptions will represent those expected to be implemented during exploration spaceflight missions(e.g.20-minute proprioceptive training sessions3 times per week). RELEVANCE The deliverable from this project will be a proof-of-concept countermeasure design that has been fully assessed for efficacy in a spaceflight analog. The findings and lessons learned from this study will be translated for validation of this countermeasure on the ISS. An effective countermeasure will be added to the suite of operationally implemented in-flight sensorimotor countermeasures.

T R Macaulay↗

Sensitivity analysis for the dynamic response of thermoviscoplastic shells of revolution

A computational procedure is presented for evaluating the sensitivity coefficients of the dynamic axisymmetric, fully-coupled, thermoviscoplastic response of shells of revolution. The analytical formulation is based on Reissner's large deformation shell theory with the effects of large-strain, transverse shear deformation, rotatory inertia and moments turning around the normal to the middle surface included. The material model is chosen to be viscoplasticity with strain hardening and thermal hardening, and an associated flow rule is used with a von Mises effective stress. A mixed formulation is used for the shell equations with the fundamental unknowns consisting of six stress resultants, three generalized displacements and three velocity components. The energy-balance equation is solved using a Galerkin procedure, with the temperature as the fundamental unknown. Spatial discretization is performed in one dimension (meridional direction) for the momentum and constitutive equations of the shell, and in two dimensions (meridional and thickness directions) for the energy-balance equation. The temporal integration is performed by using an explicit central difference scheme (leap-frog method) for the momentum equation; a predictor-corrector version of the trapezoidal rule is used for the energy-balance equation; and an explicit scheme consistent with the central difference method is used to integrate the constitutive equations. The sensitivity coefficients are evaluated by using a direct differentiation approach. Numerical results are presented for a spherical cap subjected to step loading.

Kulkarni, Makarand↗

The energetics and dynamics of confinement in flexible frameworks and molecular confinement

Porous frameworks form the chemical and structural basis for critical technologies in separations, catalysis, nuclear waste containment and biomedical applications. Hundreds of zeolites and metal organic frameworks (MOFs) have been synthesized, and their ability to separate and store hydrogen, methane and carbon dioxide has been investigated both experimentally and theoretically. Nevertheless, a fundamental and systematic molecular-level understanding of the thermodynamic and structural factors governing the stability and guest-host interactions in these materials lags behind focused studies of specific systems. Because the guest molecules interact with each other and with the host framework, molecular confinement is a finely balanced and complex phenomenon. The ability of the guest molecules to bind and diffuse through the pores is determined by the nature of the host framework which, in turn, responds to the nature and concentration of guest molecules and to pressure and temperature. The work explores how framework flexibility, tailored by structure, composition, temperature and pressure, is a general phenomenon, similar in nature but variable in extent, in both zeolites and MOFs and is part of a free energy landscape in which framework-guest interactions, pressure, and temperature result in changes in framework geometry and, in some cases, phase transitions. These subtle and/or pronounced changes in lattice geometry, energetics, and dynamics can play a decisive role in confinement and in differentiating the binding of molecules of similar size. The free energy landscape created by these structural changes links polymorphism, amorphization, “breathing,” “gate opening” and confinement. Specifically, the generality of such behavior arises from commonalities in lattice dynamics and energetics of frameworks containing a combination of strong rigid bonds and weaker more flexible deformation modes. Identifying and describing these common and collective phenomena is the focus of the research on a selected group of zeolites and MOFs. Structural studies using X-ray and neutron diffraction explore the mechanical functionality of these important materials, specifically how framework materials respond to changes in temperature, pressure and guest loading. These structural studies are combined with calorimetric measurements, using techniques uniquely developed in the participating laboratories, of heats of formation, heat capacities and entropies, and guest-host interactions. The experimental thermodynamic studies are complemented by inelastic neutron scattering studies of the lattice dynamics related both to framework vibrations and to guest-host interactions. The report below summarizes the work done at UC Davis, which is complemented by work done at BYU (Woodfield) and Virginia Tech (Ross).

36 MATERIALS SCIENCE↗

The energetics and dynamics of confinement in flexible frameworks and molecular confinement

Porous frameworks form the chemical and structural basis for critical technologies in separations, catalysis, nuclear waste containment and biomedical applications. Hundreds of zeolites and metal organic frameworks (MOFs) have been synthesized, and their ability to separate and store hydrogen, methane and carbon dioxide has been investigated both experimentally and theoretically. Nevertheless, a fundamental and systematic molecular-level understanding of the thermodynamic and structural factors governing the stability and guest-host interactions in these materials lags behind focused studies of specific systems. Because the guest molecules interact with each other and with the host framework, molecular confinement is a finely balanced and complex phenomenon. The ability of the guest molecules to bind and diffuse through the pores is determined by the nature of the host framework which, in turn, responds to the nature and concentration of guest molecules and to pressure and temperature. The work explores how framework flexibility, tailored by structure, composition, temperature and pressure, is a general phenomenon, similar in nature but variable in extent, in both zeolites and MOFs and is part of a free energy landscape in which framework-guest interactions, pressure, and temperature result in changes in framework geometry and, in some cases, phase transitions. These subtle and/or pronounced changes in lattice geometry, energetics, and dynamics can play a decisive role in confinement and in differentiating the binding of molecules of similar size. The free energy landscape created by these structural changes links polymorphism, amorphization, “breathing,” “gate opening” and confinement. Specifically, the generality of such behavior arises from commonalities in lattice dynamics and energetics of frameworks containing a combination of strong rigid bonds and weaker more flexible deformation modes. Identifying and describing these common and collective phenomena is the focus of the research on a selected group of zeolites and MOFs. Structural studies using X-ray and neutron diffraction explore the mechanical functionality of these important materials, specifically how framework materials respond to changes in temperature, pressure and guest loading. These structural studies are combined with calorimetric measurements, using techniques uniquely developed in the participating laboratories, of heats of formation, heat capacities and entropies, and guest-host interactions. The experimental thermodynamic studies are complemented by inelastic neutron scattering studies of the lattice dynamics related both to framework vibrations and to guest-host interactions. This research was a collaboration between UC Davis (A. Navrotsky) BYU (B. Woodfield) and Virginia Tech (N. Ross).

36 MATERIALS SCIENCE↗

Scalable multiscale modeling of platelets with 100 million particles

Here, we developed the core components of the AI-aided multiple time stepping algorithm for multiscale modeling of cell dynamics. This algorithm was implemented and analyzed on two supercomputer architectures with an application of simulating the aggregation of 250 platelets, or 102 million particles. To scale on these computers with complex memory and network architectures with GPUs, we devised a biomechanics-informed task mapping scheme to optimize load imbalance, communications, and memory utilization. Our simulations, scaling well up to 192 nodes on a Summit-like supercomputer with a peak speed of 11 petaflops, achieved a rate of 423 μs/day which is 500 times faster than the conventional algorithm using static time step and this has enabled studies of record size blood clots at record spatial–temporal resolutions. Additionally, we discovered the sensitive dependence of the scalability and execution time on the methods of decomposition, CPU–GPU coupling, and task mapping.

97 MATHEMATICS AND COMPUTING↗