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DOE OSTI2025

SpecSims: A Scalable Speculative Tree-based Simulation Cloning Framework for Finite Memory Machines

Simulation cloning is a technique in which cloned simulations whose state spaces differ partially from their parent simulation due to intervening events are spawned at runtime and concurrently advanced. It is a powerful method to carry out what-if analysis by speculatively exploring and evaluating the impact of various permutations of intervening cascade of events. Due to the exponential growth in the number of possible clones even for a small number of distinct intervening events, the practical efficacy of the approach is often severely limited by the maximum available memory of the computing host. In this paper, we introduce a novel speculative simulation cloning framework that executes a simulation cloning campaign capable of efficiently exploring an exponentially large space of clone simulations created by permutation of intervening events under a finite memory constraint. We provide a theoretical analysis of the runtime characteristics of our proposed approach and highlight its novel advantages such as memory-aware and as-long-as-needed execution. Furthermore, in support of our analytical findings and to demonstrate its practical feasibility, we implement a prototype of the cloning framework on a shared memory system and report its performance characteristics in the context of a heat diffusion simulation, and a power grid simulation subject to cascading disruptions from geomagnetic disturbances.

Simulation framework↗

DOE OSTI2026

Differences in cluster and internal wake effects from mesoscale and large-eddy simulations off the US East Coast

Mesoscale simulations are increasingly used to estimate wake effects within and between large wind farms, despite limited validation for large-scale wake effects. This study evaluates the capabilities and limitations of mesoscale simulations in capturing wake-induced impacts on wind turbine power production through a direct comparison with large-domain large-eddy simulations (LESs) for three planned offshore wind farms under realistic atmospheric conditions and a range of atmospheric stabilities. We assess mesoscale performance in replicating wake characteristics behind single and multiple turbine clusters and quantify the resulting variability in mean turbine power. Results show that mesoscale Weather Research and Forecasting simulations with the Fitch wind farm parameterization capture key features of the velocity deficit downstream of both single and multiple wind farms, with mean root-mean-square errors near 5 % and good agreement with stability-driven wake behavior. However, in these simulations, the mesoscale Fitch parameterization underestimates power losses from internal wake effects, particularly when turbines align with the prevailing wind direction or under stable stratification. In these conditions, individual wakes persist and dominate downstream power deficits. The coarse resolution of the mesoscale simulations limits their ability to resolve individual wind turbine wakes that drive power fluctuations within wind farms. Nonetheless, mesoscale simulations can yield accurate estimates of combined wake losses from internal and cluster effects across some wind direction sectors, where errors in wake representation may cancel each other out. These findings underscore the strengths of mesoscale simulations for capturing broader wake patterns while highlighting their limitations for modeling turbine-level power losses. Future work should explore hybrid modeling approaches to capture both long-range cluster wake propagation and localized internal wake dynamics.

17 WIND ENERGY↗

DOE OSTI2018

On the Need for a Unified and Collaboratively Developed Residential Building Simulation Platform: Preprint

Residential building energy simulations are becoming ever more pervasive; they form the basis of energy efficient building design, zero energy goals, codes and standards, home certification and ratings industries, utility programs, regional/state planning, and technology assessments. And yet the residential building simulation community is highly fragmented with a patchwork of simulation engines with varying models, inputs, assumptions, and results. This inconsistency degrades confidence in these tools, increases industry-wide development and maintenance costs, and slows the availability of new efficiency technology models. The need for collaboration on an impartial, transparent, and capable residential building simulation platform has never been greater. But to develop and maintain a state-of-the-art simulation platform requires a dedicated and sustained investment. By leveraging existing resources and expertise from multiple entities/regions, a unified and collaboratively developed simulation platform can provide increased levels of energy efficiency at an accelerated pace. This paper presents the advantages and disadvantages of a unified residential building simulation platform in relationship to four real-world examples (RESNET HERS ratings, utility programs, California's Title 24, and DOE). The paper covers recent developments and improved capabilities that may move us closer to an ideal simulation platform and what challenges remain. The hope is to spur a frank and honest dialogue about how to work together towards the vision of achieving deeper and more reliable energy savings in the residential buildings industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

On the Need for a Unified and Collaboratively Developed Residential Building Simulation Platform

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗

DOE OSTI2023

Simulation of evapotranspiration and yield of maize: An inter-comparison among 41 maize models

Accurate simulation of crop water use (evapotranspiration, ET) can help crop growth models to assess the likely effects of climate change on future crop productivity, as well as being an aid for irrigation scheduling for today's growers. To determine how well maize (Zea mays L.) growth models can simulate ET, an initial inter-comparison study was conducted in 2019 under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Herein, we present results of a second inter-comparison study of 41 maize models that was conducted using more comprehensive datasets from two additional sites - Mead, Nebraska, USA and Bushland, Texas, USA. There were 20 treatment-years with varying irrigation levels over multiple seasons at both sites. ET was measured using eddy covariance at Mead and using large weighing lysimeters at Bushland. A wide range in ET rates was simulated among the models, yet several generally were able to simulate ET rates adequately. The ensemble median values were generally close to the observations, but a few of the models sometimes performed better than the median. Many of the models that did well at simulating ET for the Mead site did poorly for drier, windy days at the Bushland site, suggesting they need to improve how they handle humidity and wind. Additional variability came from the approaches used to simulate soil water evaporation. Fortunately, several models were identified that did well at simulating soil water evaporation, canopy transpiration, biomass accumulation, and grain yield. These models were older and have been widely used, which suggests that a larger number of users have tested these models over a wider range of conditions leading to their improvement. These revelations of the better approaches are leading to model improvements and more accurate simulations of ET.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Development and case study of the liquid desiccant system module in sorption system simulation program (SorpSim)

Liquid desiccant systems (LDS) have recently seen an increase in research interest as they can utilize low-grade heat resources and separate the sensible and latent cooling loads by efficiently removing moisture in the air without cooling it to the dew point. Yet, simulation and analysis of LDS had remained complex and demanding due to the limited resources of LDS simulation tools. This work presents the new LDS module developed in the Sorption system Simulation program (SorpSim), which is an open-source and flexible platform for steady-state simulation and analysis of various sorption systems. First, the new LDS module containing a finite-difference model and an effectiveness-NTU model for the heat and mass transfer in LDS dehumidifier/regenerator component was introduced. Then the simulation results of the new module were verified using data from the literature. Lastly, a case study was carried out in SorpSim where an LDS cycle was built and simulated using the new module. The impacts of design and operating parameters on the simulated LDS performance were investigated. The parametric study revealed that a high source temperature improved moisture removal rate (MRR) but reduced the system coefficient of performance (COP); the COP increased monotonically with the desiccant solution recirculation ratio, while the MRR peaked at a ratio of 85%; and an internal solution heat exchanger with UA of 800 W/K was found to be sufficient for optimal performance under high recirculation ratios. The case study demonstrated the LDS module’s capability to facilitate the analysis of LDS design and operation. The LDS module can be further coupled with other component models in SorpSim to simulate and analyze various liquid-desiccant-based systems.

42 ENGINEERING↗

DOE OSTI2017

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial “patches” distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Lowering entry barriers to developing custom simulators of distributed applications and platforms with SimGrid

Researchers in parallel and distributed computing (PDC) often resort to simulation because experiments conducted using a simulator can be for arbitrary experimental scenarios, are less resource-, labor-, and time-consuming than their real-world counterparts, and are perfectly repeatable and observable. Many frameworks have been developed to ease the development of PDC simulators, and these frameworks provide different levels of accuracy, scalability, versatility, extensibility, and usability. Further, the SimGrid framework has been used by many PDC researchers to produce a wide range of simulators for over two decades. Its popularity is due to a large emphasis placed on accuracy, scalability, and versatility, and is in spite of shortcomings in terms of extensibility and usability. Although SimGrid provides sensible simulation models for the common case, it was difficult for users to extend these models to meet domain-specific needs. Furthermore, SimGrid only provided relatively low-level simulation abstractions, making the implementation of a simulator of a complex system a labor-intensive undertaking. In this work we describe developments in the last decade that have contributed to vastly improving extensibility and usability, thus lowering or removing entry barriers for users to develop custom SimGrid simulators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Impact of detector simulation in particle physics collider experiments

Through the last three decades, precise simulation of the interactions of particles with matter and modeling of detector geometries has proven to be of critical importance to the success of the international high-energy physics experimental programs. For example, the detailed detector modeling and accurate physics of the Geant4-based simulation software of the CMS and ATLAS particle physics experiments at the European Center of Nuclear Research (CERN) Large Hadron Collider (LHC) was a determinant factor for these collaborations to deliver physics results of outstanding quality faster than any hadron collider experiment ever before. This review article highlights the impact of detector simulation on particle physics collider experiments. It presents numerous examples of the use of simulation, from detector design and optimization, through software and computing development and testing, to cases where the use of simulation samples made a difference in the accuracy of the physics results and publication turnaround, from data-taking to submission. It also presents the economic impact and cost of simulation in the CMS experiment. Future experiments will collect orders of magnitude more data, taxing heavily the performance of simulation and reconstruction software for increasingly complex detectors. Consequently, it becomes urgent to find solutions to speed up simulation software in order to cope with the increased demand in a time of flat budgets. The study ends with a short discussion on the potential solutions that are being explored, by leveraging core count growth in multicore machines, using new generation coprocessors, and re-engineering of HEP code for concurrency and parallel computing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

Atomic configurations of glassy or amorphous materials containing medium-range order (MRO) may be identified by comparing fluctuation transmission electron microscopy (FTEM) measurements to FTEM simulations obtained using model configurations. Candidate model sizes have traditionally been much thinner than the samples measured experimentally, and publicly available FTEM simulation software has until now omitted microscope parameters, dynamical scattering, and the phase of the diffracted electron wave. We introduce MS–STEM–FEM, an open-source software package for simulating FTEM experiments using established multi-slice TEM simulation techniques to emulate experiment more closely by incorporating microscope parameters and simulating electron scattering and propagation as a complex valued wave. Simulations using established models are compared with results of experimental STEM–FEM to validate the software. Several statistical measures of diffraction are implemented and their responses to model features are compared. Dynamical scattering is found to be less influential than the variety of crystallite orientations which occur in thicker models. Simulations of variable resolution microscopy confirm that cumulative intensity of the FTEM signal decreases with reduced model MRO and increased coherence volume. In conclusion, advantageous model scaling characteristics and efficient processor performance scaling are demonstrated, along with a study of convergence with respect to pertinent simulation parameters to identify accuracy requirements.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States

Abstract Regional climate simulations over the continental United States were conducted for the 2011 warm season using the Weather Research and Forecasting model at convection‐permitting resolution (4 km) with two commonly used microphysics parameterizations (Thompson and Morrison). Sensitivities of the simulated mesoscale convective system (MCS) properties and feedbacks to large‐scale environments are systematically examined against high‐resolution geostationary satellite and 3‐D mosaic radar observations. MCS precipitation including precipitation amount, diurnal cycle, and distribution of hourly precipitation intensity are reasonably captured by the two simulations despite significant differences in their simulated MCS properties. In general, the Thompson simulation produces better agreement with observations for MCS upper level cloud shield and precipitation area, convective feature horizontal and vertical extents, and partitioning between convective and stratiform precipitation. More importantly, Thompson simulates more stratiform rainfall, which agrees better with observations and results in top‐heavier heating profiles from robust MCSs compared to Morrison. A stronger dynamical feedback to the large‐scale environment is therefore seen in Thompson, wherein an enhanced mesoscale vortex behind the MCS strengthens the synoptic‐scale trough and promotes advection of cool and dry air into the rear of the MCS region. The latter prolongs the MCS lifetimes in the Thompson relative to the Morrison simulations. Hence, different treatment of cloud microphysics not only alters MCS convective‐scale dynamics but also has significant impacts on their macrophysical properties such as lifetime and precipitation. As long‐lived MCSs produced 2–3 times the amount of rainfall compared to short‐lived ones, cloud microphysics parameterizations have profound impact in simulating extreme precipitation and the hydrologic cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Cusps in the center of galaxies: a real conflict with observations or a numerical artefact of cosmological simulations?

Galaxy observations and N-body cosmological simulations produce conflicting dark matter halo density profiles for galaxy central regions. While simulations suggest a cuspy and universal density profile (UDP) of this region, the majority of observations favor variable profiles with a core in the center. In this paper, we investigate the convergency of standard N-body simulations, especially in the cusp region, following the approach proposed by [1]. We simulate the well known Hernquist model using the SPH code Gadget-3 and consider the full array of dynamical parameters of the particles. We find that, although the cuspy profile is stable, all integrals of motion characterizing individual particles suffer strong unphysical variations along the whole halo, revealing an effective interaction between the test bodies. This result casts doubts on the reliability of the velocity distribution function obtained in the simulations. Moreover, we find unphysical Fokker-Planck streams of particles in the cusp region. The same streams should appear in cosmological N-body simulations, being strong enough to change the shape of the cusp or even to create it. Our analysis, based on the Hernquist model and the standard SPH code, strongly suggests that the UDPs generally found by the cosmological N-body simulations may be a consequence of numerical effects. A much better understanding of the N-body simulation convergency is necessary before a 'core-cusp problem' can properly be used to question the validity of the CDM model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Refining fast calorimeter simulations with a Schrödinger Bridge

Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a fraction of the generation time. Nearly all methods proposed so far learn neural networks that map a random variable with a known probability density, like a Gaussian, to realistic-looking events. In many cases, physics events are not close to Gaussian and so these neural networks have to learn a highly complex function. We study an alternative approach: Schrödinger bridge Quality Improvement via Refinement of Existing Lightweight Simulations (SQuIRELS). SQuIRELS leverages the power of diffusion-based neural networks and Schrödinger bridges to map between samples where the probability density is not known explicitly. We apply SQuIRELS to the task of refining a classical fast simulation to approximate a full classical simulation. On simulated calorimeter events, we find that SQuIRELS is able to reproduce highly non-trivial features of the full simulation with a fraction of the generation time.

Calorimeter methods↗

DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Evaluation of the Inertial Response of Variable-Speed Wind Turbines Using Advanced Simulation

In this paper, we focus on the temporary frequency support effect provided by wind turbine generators (WTGs) through the inertial response. With the implemented inertial control methods, the WTG is capable of increasing its active power output by releasing parts of the stored kinetic energy when the frequency excursion occurs. The active power can be boosted temporarily above the maximum power points, but the rotor speed deceleration follows and an active power output deficiency occurs during the restoration of rotor kinetic energy. We evaluate and compare the inertial response induced by two distinct inertial control methods using advanced simulation. In the first stage, the proposed inertial control methods are analyzed in offline simulation. Using an advanced wind turbine simulation program, FAST with TurbSim, the response of the researched wind turbine is comprehensively evaluated under turbulent wind conditions, and the impact on the turbine mechanical components are assessed. In the second stage, the inertial control is deployed on a real 600kW wind turbine - Controls Advanced Research Turbine, 3-bladed (CART3), which further verifies the inertial control through a hardware-in-the-loop (HIL) simulation. Various inertial control methods can be effectively evaluated based on the proposed two-stage simulation platform, which combines the offline simulation and real-time HIL simulation. The simulation results also provide insights in designing inertial control for WTGs.

17 WIND ENERGY↗

DOE OSTI2021

Quasi-Static Time Series Fatigue Simulation for PV Inverter Semiconductors with Long-Term Solar Profile

Power system simulations with long-term data tend to have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stresses cycle is with line frequency. This requires the time step of the fatigue simulation to be much smaller than the line period. This small time step results in poor simulation speed, especially for long-term simulations. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The fatigue analysis typically focuses on the peak and valley values of a strain and neglect the transients from peaks to valleys. The proposed simulation utilizes this property of fatigue analysis and calculates the steady state of the semiconductor junction temperature only. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset without losing accuracy.

fast simulation↗

DOE OSTI2022

Electromagnetic Transient (EMT) Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (T&D Models)

Simulation of high-fidelity models of extreme fast charging (XFC) systems and large-area power grids with many XFCs can be time consuming in traditional simulators. Traditional simulators use a single method of discretization for all the components that results in imposing a large computational burden of inverting a large matrix as well as increased computations related to single method of discretization (that is typically a trapezoidal method). To overcome the problem of simulating large-area power grids with many XFCs, in this paper, advanced numerical simulation algorithms are applied for the first time together to reduce the dimension of matrix inversion. Here, the algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. These algorithms apply multiple discretization algorithms rather than a single discretization algorithm that further reduces the computational burden. The approaches mentioned here have resulted in speed-up of up to 18x in the simulation of a single distribution system with 15 XFCs and of up to 271x in the simulation of a transmission-distribution system with 300 XFCs in multiple distribution feeders with respect to conventional simulators (like power systems computer aided design [PSCAD]).

42 ENGINEERING↗