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At least 973 records · Page 54

Zinc binding alters the conformational dynamics and drives the transport cycle of the cation diffusion facilitator YiiP

YiiP is a secondary transporter that couples Zn 2+ transport to the proton motive force. Structural studies of YiiP from prokaryotes and Znt8 from humans have revealed three different Zn 2+ sites and a conserved homodimeric architecture. These structures define the inward-facing and outward-facing states that characterize the archetypal alternating access mechanism of transport. To study the effects of Zn 2+ binding on the conformational transition, we use cryo-EM together with molecular dynamics simulation to compare structures of YiiP from Shewanella oneidensis in the presence and absence of Zn 2+ . To enable single-particle cryo-EM, we used a phage-display library to develop a Fab antibody fragment with high affinity for YiiP, thus producing a YiiP/Fab complex. To perform MD simulations, we developed a nonbonded dummy model for Zn 2+ and validated its performance with known Zn 2+ -binding proteins. Using these tools, we find that, in the presence of Zn 2+ , YiiP adopts an inward-facing conformation consistent with that previously seen in tubular crystals. After removal of Zn 2+ with high-affinity chelators, YiiP exhibits enhanced flexibility and adopts a novel conformation that appears to be intermediate between inward-facing and outward-facing states. This conformation involves closure of a hydrophobic gate that has been postulated to control access to the primary transport site. Comparison of several independent cryo-EM maps suggests that the transition from the inward-facing state is controlled by occupancy of a secondary Zn 2+ site at the cytoplasmic membrane interface. This work enhances our understanding of individual Zn 2+ binding sites and their role in the conformational dynamics that govern the transport cycle.

59 BASIC BIOLOGICAL SCIENCES↗

Baycal

Bayesian Model Calibration (BayCal) toolkit is a software plugin for Risk Analysis Virtual Environment (RAVEN) framework, arming at inversely quantifying the uncertainties associated with simulation model parameters based on available experiment data. BayCal seeks statistical inference of the uncertain input parameters that are consistent with the available measurement data or observed data. The unique feature of BayCal is the capability to be linked with RAVEN to build corresponding calibration workflows for complex multi-physics simulations. In addition to be able to use the machine learning capability of RAVEN to significantly reduce the computational cost of expensive simulation models, another distinctive feature of BayCal is the capability to deal with high-dimensional correlated model outputs, such as time series observations at multiple locations, via principal component analysis (PCA) technique.

Wang, Congjian↗

The architecture of Newton, a general-purpose dynamics simulator

The architecture for Newton, a general-purpose system for simulating the dynamics of complex physical objects, is described. The system automatically formulates and analyzes equations of motion, and performs automatic modification of this system equations when necessitated by changes in kinematic relationships between objects. Impact and temporary contact are handled, although only using simple models. User-directed influence of simulations is achieved using Newton's module, which can be used to experiment with the control of many-degree-of-freedom articulated objects.

Cremer, James F.↗

Coupled charge and energy transfer dynamics in light harvesting complexes from a hybrid hierarchical equations of motion approach

Here, we describe a method for simulating exciton dynamics in protein–pigment complexes, including effects from charge transfer as well as fluorescence. The method combines the hierarchical equations of motion, which are used to describe quantum dynamics of excitons, and the Nakajima–Zwanzig quantum master equation, which is used to describe slower charge transfer processes. We study the charge transfer quenching in light harvesting complex II, a protein postulated to control non-photochemical quenching in many plant species. Using our hybrid approach, we find good agreement between our calculation and experimental measurements of the excitation lifetime. Furthermore, our calculations reveal that the exciton energy funnel plays an important role in determining quenching efficiency, a conclusion we expect to extend to other proteins that perform protective excitation quenching. This also highlights the need for simulation methods that properly account for the interplay of exciton dynamics and charge transfer processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗

Forward Bay Cover Separation Modeling and Testing for the Orion Multi-Purpose Crew Vehicle

Spacecraft multi‐body separation events during atmospheric descent require complex testing and analysis to validate the flight separation dynamics model and to verify no recontact. NASA Orion Multi‐Purpose Crew Vehicle (MPCV) teams examined key model parameters and risk areas to develop a robust but affordable test campaign in order to validate and verify the Forward Bay Cover (FBC) separation event for Exploration Flight Test‐1 (EFT‐1). The FBC jettison simulation model is highly complex, consisting of dozens of parameters varied simultaneously, with numerous multi‐parameter interactions (coupling and feedback) among the various model elements, and encompassing distinct near‐field, mid‐field, and far‐field regimes. The test campaign was composed of component‐level testing (for example gas‐piston thrusters and parachute mortars), ground FBC jettison tests, and FBC jettison air‐drop tests that were accomplished by a highly multi‐disciplinary team. Three ground jettison tests isolated the testing of mechanisms and structures to anchor the simulation models excluding aerodynamic effects. Subsequently, two air‐drop tests added aerodynamic and parachute parameters, and served as integrated system demonstrations, which had been preliminarily explored during the Orion Pad Abort‐1 (PA‐1) flight test in May 2010. Both ground and drop tests provided extensive data to validate analytical models and to verify the FBC jettison event for EFT‐1, but more testing is required to support human certification, for which NASA and Lockheed Martin are applying knowledge from Apollo and EFT‐1 testing and modeling to develop a robust but affordable human spacecraft capability.

Ali, Yasmin↗

High Fidelity Simulations of a Methane-Oxygen Rotating Detonation Rocket Engine

The rotating detonation combustor (RDC) is an important realization of pressure gain combustion for practical applications. The RDC system is characterized by a highly unsteady flow field, with multiple reflected pressure waves following the strong detonations and the existence of partially-burnt gases entrained within the detonation annulus during the injector recovery process. While experimental efforts have provided macroscopic properties of an RDC with a given fuel-oxidizer mixture and geometry, limited optical access and reduced lifespan of flow-field diagnostic equipment constrain understanding of the mechanisms that lend to wave stability, controllability, and sustainability. To this end, high-fidelity numerical simulations of the Air Force Research Laboratory (AFRL) methane-oxygen rotating detonation rocket engine (RDRE) are performed to provide detailed insight into the detonation physics and anomalous behavior within the combustor. The results highlight the merit of high-fidelity numerical studies in analyzing the combustion processes and injector dynamics of a complex combustion system. The simulations capture the general wave behavior observed within the experimental studies. Three different operating conditions, with varying global equivalence ratio and system mass flow rate, are considered: (1) baseline configuration, (2) high equivalence ratio, and (3) high mass flow rate. The high mass flow rate case results in increased detonation wave strength whereas the high equivalence ratio results in increased deflagrative heat release. The high equivalence ratio case results in chaotic behavior with two pairs of counter-rotating detonation waves, whereas a single pair of co-rotating waves is observed in the baseline and high mass flow rate cases. Further, parasitic combustion of the reactant mixture ahead of the detonation wave diminishes its strength and reduces propagation speed to approximately 50-60\% of the Chapman-Jouguet (CJ) condition. In this work, a detailed analysis of the detonation wave behavior, injector dynamics, and the statistics of combustion parameters are presented.

Prakash, Supraj↗

Improving transient analysis technology for aircraft structures

Aircraft dynamic analyses are demanding of computer simulation capabilities. The modeling complexities of semi-monocoque construction, irregular geometry, high-performance materials, and high-accuracy analysis are present. At issue are the safety of the passengers and the integrity of the structure for a wide variety of flight-operating and emergency conditions. The technology which supports engineering of aircraft structures using computer simulation is examined. Available computer support is briefly described and improvement of accuracy and efficiency are recommended. Improved accuracy of simulation will lead to a more economical structure. Improved efficiency will result in lowering development time and expense.

Melosh, R. J.↗

Spatiotemporal pattern detection, generation, and computation with circuits

Abstract Implementations of neurons, delays, and synapse circuits are presented with simulations. These neural elements are used to create two small spiking neural networks, the Rate-Window and Order-Biased clusters, which are capable of detecting simple two-spike spatiotemporal patterns. A simple pattern detecting network (SPDN) is created by combining the Rate-Window and Order-Biased clusters, where clusters are small spiking neural networks, and its simple pattern detection ability is demonstrated in simulation. The SPDN is used to implement a complex pattern detecting network (CPDN) and its complex pattern detection ability is demonstrated in simulation. Methods for generating arbitrary spatiotemporal patterns are presented. The CPDN and spatiotemporal pattern generation methods are then used to implement a novel spatiotemporal computing paradigm based on detecting and responding to spatiotemporal symbols. A simulation of a spatiotemporal half adder is presented to demonstrate the computing paradigm.

97 - MATHEMATICS AND COMPUTING↗

SiC Receiver/Reactor by Additive Manufacturing for Concentrated Solar Thermocatalysis with Thermal Energy Storage (Final Technical Report - Public)

The direct use of solar thermal energy provides opportunities for low-cost heating sources for a variety of applications. Ultra-high temperatures around 1000°C are high value and highly useful for energy-demanding industries. Many materials cannot withstand these conditions. In the area of Sustainable Chemicals, further limitations on material stability exist. Combining state-of-the-art materials with new designs provides a promising pathway for harvesting solar thermal energy and performing high temperature chemical processes. However, conventional manufacturing limits the potential for design flexibility. In this project, Additive Manufacturing was combined with advanced materials and new chemical reactor designs. In addition, 24/7 energy is necessary for chemical processing, and designs for ultra-high temperature thermal storage were devised. Specifically, preliminary design of a novel solar thermal receiver was developed in this project and designed to work with thermocatalytic reactors for producing sustainable chemicals and fuels. An ultra-high temperature particle storage system and heat exchangers were proposed to transport ultra-hot air as thermal fluid for the system. On a broader scale, this system could be used to tap solar thermal energy for a centralized facility with capability of transferring that heat to various segments at a full range of temperatures to 1000°C. The project pushed the temperature boundaries past those in current use, and Additive Manufacturing was envisaged for fabricating the receiver to meet requirements of extreme environments. An extensive analysis of silicon carbide additive manufacturing was performed to compare the thermal and mechanical properties of complex geometries compared to conventional material and those manufactured via other methods. The Additive Manufacturing via Binder-Jet printing was optimized and characterized to provide high quality and reproducible components capable of withstanding the proposed extreme environments. The designs for the concentrating solar thermal cavity with ultra-hot air thermal fluid showed high performance in simulations, attributable to the complex optimized geometries of the 3D printed systems. The bright future of Additive Manufacturing with advanced materials developments should provide more options and even higher quality as the technology further develops. Current costs for Additive Manufacturing of advanced ceramics is relatively low, however post-processing of the materials for extreme environments is currently high. There is little industrial-scale infrastructure for these, but it is growing as niche applications become more mainstream. The results of the project can be translated into similar extreme environments for concentrating solar thermal energy as well as its integration with ultra-hot air thermal fluids. A number of industries that require ultra-high temperatures need to electrify or otherwise decarbonize for climate goals, and this project showed that theoretically there is a pathway to do so with direct concentrated solar thermal power.

10 SYNTHETIC FUELS↗

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

Simon, Dan↗

Viscous simulation method for unsteady flows past multicomponent configurations

The present algorithm for the numerical simulation of flows about complex configurations (whose multiple and nonsimilar components have arbitraty geometries) employs a hybridization of the domain decomposition techniques for grid generation as well as to reduce computer-memory requirements. A fully vectorized, finite-volume, upwind-biased, approximately factored multigrid method is used to solve 3D Reynolds-averaged unsteady and compressible Navier-Stokes equations simulating supersonic flows past an ogive-nose-cylinder near or within a cavity. The time-averaged surface pressures obtained compare favorably with the wind tunnel data.

Fouladi, Kamran↗

Simulations of surface winds at the Viking Lander sites using a one-level model

The one-level model developed by Mass and Dempsey for use in predicting surface flows in regions of complex terrain was adapted to simulate surface flows at the Viking lander sites on Mars. In the one-level model, prediction equations for surface winds and temperatures are formulated and solved. Surface temperatures change with time in response to diabatic heating, horizontal advection, adiabatic heating and cooling effects, and horizontal diffusion. Surface winds can change in response to horizontal advection, pressure gradient forces, Coriolis forces, surface drag, and horizontal diffusion. Surface pressures are determined by integration of the hydrostatic equation from the surface to some reference level. The model has successfully simulated surface flows under a variety of conditions in complex-terrain regions on Earth.

Bridger, Alison F. C.↗

PyTrac

SAND2025-00635O PyTrac is a software tool that analyzes and visualizes PTRAC event files generated by MCNP 6.3. It converts these files into a graph network that makes it easier to interpret individual histories. The software includes command line tools for viewing the graph data structure in both 2D and 3D formats. PyTrac also integrates with MCNP to run simulations and manage data files. This provides a streamlined approach to analyzing and understanding the complex data generated by MCNP simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nowack, Aaron [Sandia National Lab. (SNL-CA), Live↗

MOS integrated circuit fault modeling

Three digital simulation techniques for MOS integrated circuit faults were examined. These techniques embody a hierarchy of complexity bracketing the range of simulation levels. The digital approaches are: transistor-level, connector-switch-attenuator level, and gate level. The advantages and disadvantages are discussed. Failure characteristics are also described.

Sievers, M.↗

SAFSIM overview

An overview of the systems analysis flow simulator (SAFSIM) computer program is provided. SAFSIM is being developed at Sandia National Laboratories and is currently funded by the Air Force Space Nuclear Thermal Propulsion (SNTP) Program. SAFSIM is a general purpose, Fortran computer program to simulate the integrated performance of complex systems involving fluid mechanics, heat transfer, and reactor dynamics. SAFSIM provides sufficient versatility to allow the engineering simulation of almost any system. SAFSIM is based on a 1-D finite element model and provides the analyst with approximate solutions to complex problems.

Dobranich, Dean↗

The 17 April 2021 Widespread Solar Energetic Particle Event

A complex and long-lasting solar eruption on 17 April 2021 produced a widespread solar energetic particle (SEP) event that was observed by five longitudinally well-separated observers in the inner heliosphere that covered distances to the Sun from 0.42 to 1 au: BepiColombo, Parker Solar Probe, Solar Orbiter, STEREO A, and near-Earth spacecraft. The event was the second widespread SEP event detected in solar cycle 25, and it produced relativistic electrons and protons. It was associated with a long-lasting solar hard X-ray flare that showed multiple hard X-ray peaks over a duration of one hour. The event was further accompanied by a medium-fast coronal mass ejection (CME) with a speed of 880 km s -1 that drove a shock, an extreme ultraviolet wave, and long-lasting and complex radio burst activity that showed four distinct type III burst groups over a period of 40 min. We aim to understand the reason for the wide spread of elevated SEP intensities in the inner heliosphere as well as identify the underlying source regions of the observed energetic electrons and protons. We applied a comprehensive multi-spacecraft analysis of remote-sensing observations and in situ measurements of the energetic particles and interplanetary context to attribute the SEP observations at the different locations to the various potential source regions at the Sun. We used an ENLIL simulation to characterize the complex interplanetary state and its role in the energetic particle transport. The magnetic connection between each spacecraft and the Sun was determined using ballistic backmapping in combination with potential field source surface extrapolations in the lower corona. Using also a reconstruction of the coronal shock front, we then determined the times when the shock establishes magnetic connections with the different observers. Radio observations were used to characterize the directivity of the four main injection episodes, which were then employed in a 2D SEP transport simulation to test the importance of these different injection episodes. A comprehensive timing analysis of the inferred solar injection times of the SEPs observed at each spacecraft suggests different source processes being important for the electron and proton events. Comparison among the characteristics and timing of the potential particle sources, such as the CME-driven shock or the flare, suggests a stronger shock contribution for the proton event and a more likely flare-related source for the electron event. In contrast to earlier studies on widespread SEP events, we find that in this event an important ingredient for the wide SEP spread was the wide longitudinal range of about 110 o covered by distinct SEP injections, which is also supported by our SEP transport modeling.

sun↗

Advanced Combustion Modeling for Complex Turbulent Flows

The next generation of aircraft engines will need to pass stricter efficiency and emission tests. NASA's Ultra-Efficient Engine Technology (UEET) program has set an ambitious goal of 70% reduction of NO(x) emissions and a 15% increase in fuel efficiency of aircraft engines. We will demonstrate the state-of-the-art combustion tools developed a t Stanford's Center for Turbulence Research (CTR) as part of this program. In the last decade, CTR has spear-headed a multi-physics-based combustion modeling program. Key technologies have been transferred to the aerospace industry and are currently being used for engine simulations. In this demo, we will showcase the next-generation combustion modeling tools that integrate a very high level of detailed physics into advanced flow simulation codes. Combustor flows involve multi-phase physics with liquid fuel jet breakup, evaporation, and eventual combustion. Individual components of the simulation are verified against complex test cases and show excellent agreement with experimental data.

Ham, Frank Stanford↗