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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Simulations of cloud‐radiation interaction using large‐scale forcing derived from the CINDY/DYNAMO northern sounding array

Abstract The recently completed CINDY/DYNAMO field campaign observed two Madden‐Julian oscillation (MJO) events in the equatorial Indian Ocean from October to December 2011. Prior work has indicated that the moist static energy anomalies in these events grew and were sustained to a significant extent by radiative feedbacks. We present here a study of radiative fluxes and clouds in a set of cloud‐resolving simulations of these MJO events. The simulations are driven by the large‐scale forcing data set derived from the DYNAMO northern sounding array observations, and carried out in a doubly periodic domain using the Weather Research and Forecasting (WRF) model. Simulated cloud properties and radiative fluxes are compared to those derived from the S‐PolKa radar and satellite observations. To accommodate the uncertainty in simulated cloud microphysics, a number of single‐moment (1M) and double‐moment (2M) microphysical schemes in the WRF model are tested. The 1M schemes tend to underestimate radiative flux anomalies in the active phases of the MJO events, while the 2M schemes perform better, but can overestimate radiative flux anomalies. All the tested microphysics schemes exhibit biases in the shapes of the histograms of radiative fluxes and radar reflectivity. Histograms of radiative fluxes and brightness temperature indicate that radiative biases are not evenly distributed; the most significant bias occurs in rainy areas with OLR less than 150 W/m 2 in the 2M schemes. Analysis of simulated radar reflectivities indicates that this radiative flux uncertainty is closely related to the simulated stratiform cloud coverage. Single‐moment schemes underestimate stratiform cloudiness by a factor of 2, whereas 2M schemes simulate much more stratiform cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance. This study highlights the large sensitivity of SOA loadings to the particle-phase transformation of SOA volatility, which is neglected in most previous models.

Shrivastava, Manish↗
DOE OSTI2016

Dependence of radiation belt simulations to assumed radial diffusion rates tested for two empirical models of radial transport

Radial diffusion is one of the dominant physical mechanisms that drives acceleration and loss of the radiation belt electrons, which makes it very important for nowcasting and forecasting space weather models. In this paper, we investigate the sensitivity of the two parameterizations of the radial diffusion of Brautigam and Albert (2000) and Ozeke et al. (2014) on long-term radiation belt modeling using the Versatile Electron Radiation Belt (VERB). Following Brautigam and Albert (2000) and Ozeke et al. (2014), we first perform 1-D radial diffusion simulations. Comparison of the simulation results with observations shows that the difference between simulations with either radial diffusion parameterization is small. To take into account effects of local acceleration and loss, we perform 3-D simulations, including pitch angle, energy, and mixed diffusion. We found that the results of 3-D simulations are even less sensitive to the choice of parameterization of radial diffusion rates than the results of 1-D simulations at various energies (from 0.59 to 1.80 MeV). This result demonstrates that the inclusion of local acceleration and pitch angle diffusion can provide a negative feedback effect, such that the result is largely indistinguishable simulations conducted with different radial diffusion parameterizations. Finally, we also perform a number of sensitivity tests by multiplying radial diffusion rates by constant factors and show that such an approach leads to unrealistic predictions of radiation belt dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Effect of a Guide Field on Local Energy Conversion During Asymmetric Magnetic Reconnection: Particle-in-Cell Simulations

We use theory and simulations to study how the out-of-plane (guide) magnetic field strength modifies the location where the energy conversion rate between the electric field and the plasma is appreciable during asymmetric magnetic reconnection, motivated by observations (Genestreti et al., 2017). For weak guide fields, energy conversion is maximum on the magnetospheric side of the X line, midway between the X line and electron stagnation point. As the guide field increases, the electron stagnation point gets closer to the X line, and energy conversion occurs closer to the electron stagnation point. We motivate one possible nonrigorous approach to extend the theory of the stagnation point location to include a guidefield. The predictions are compared to two-dimensional particle-in-cell (PIC) simulations with vastly different guide fields. The simulations have upstream parameters corresponding to three events observed with Magnetospheric Multiscale (MMS). The predictions agree reasonably well with the simulation results,capturing trends with the guide field. The theory correctly predicts that the X line and stagnation points approach each other as the guide field increases. The results are compared to MMS observations, Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) observations of each event,and a global resistive-magnetohydrodynamics simulation of the 16 October 2015 event. The PIC simulation results agree well with the global observations and simulation but differ in the strong electric fields and energy conversion rates found in MMS observations. The observational, theoretical, and numerical resultssuggest that the strong electric fields observed by MMS do not represent a steady global reconnection rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Coupling reduced‐order modeling and coarse‐grained CFD‐DEM to accelerate coal gasifier simulation and optimization

Abstract High fidelity three‐dimensional (3‐D) numerical simulations of commercial‐scale coal gasifiers are very time consuming and expensive. This article proposes a reduced‐order modeling approach that uses quasi one‐dimensional (1‐D) CFD–DEM simulation results to serve as an accurate initial condition for the 3‐D simulation, which significantly shortens the physical time from several hours to minutes to achieve steady states. The 3‐D simulation employs a previously validated coarse‐grained CFD‐DEM approach, which further accelerates the simulation. Both 1‐D and 3‐D simulations adopt a particle shrinkage scheme to correctly account for the particle volume change due to chemical reaction and thus provides an accurate bed height. Comparison with available experimental measurements of the bed temperature and synthesis gas composition is used to validate the simulation. The final syngas composition and flowrates are strongly affected by the fuel or gasification agent rate and process operating conditions as expected. This approach is then used to optimize two important operating conditions (air and steam flows) to achieve specific gasifier performance goals for the production of Fischer–Tropsch synthesis gas and production of fuel gas for gas turbines.

Yu, Jia↗
DOE OSTI2021

The impact of coupled air–sea interaction on extreme East Asian summer monsoon simulation in CMIP5 models

Abstract In this study, the relationship between the ability to simulate air–sea interactions over the western North Pacific (WNP), and to reproduce the extreme East Asian summer monsoon (EASM), were investigated by comparing the performances of several global climate models (GCMs). High ranked in air–sea interaction simulation (HRA) and low ranked in air–sea interaction simulation (LRA) models were selected, according to their performance in simulating relations between sea surface temperature (SST) and precipitation over the WNP, from the ensemble of models that participated in the third and fifth phases of the Coupled Model Intercomparison Project (CMIP3, CMIP5). Compared with CMIP3 models, CMIP5 models exhibited improved simulations of the distinctive air–sea interaction over the WNP, namely, the strong atmospheric forcing on the ocean. Among CMIP5 models, HRA models, which reproduced intrinsic negative correlations between precipitation and SST over the WNP, could simulate the extreme EASM better than LRA models. In particular, HRA models generated a more realistic spatial distribution of the extreme EASM compared with LRA models. The defects of the LRA models resulted from distorted synoptic fields, including underestimated geopotential height and overestimated low‐level wind over the WNP, inducing unrealistic moisture supply and convection due to the exaggerated SST forcing. In contrast, reasonable air–sea interactions represented in HRA models lead to realistic synoptic fields over the WNP, and proper simulation of the extreme EASM.

Kim, Taehyung↗
DOE OSTI2025

Efficient Simulation of Open Quantum Systems on NISQ Trapped‐Ion Hardware

Abstract Simulating open quantum systems, which interact with external environments, presents significant challenges on noisy intermediate‐scale quantum (NISQ) devices due to limited qubit resources and noise. In this study, an efficient framework is proposed for simulating open quantum systems on NISQ hardware by leveraging a time‐perturbative Kraus operator representation of the system's dynamics. This approach avoids the computationally expensive Trotterization method and exploits the Lindblad master equation to represent time evolution in a compact form, particularly for systems satisfying specific commutation relations. The efficiency of this method is demonstrated by simulating quantum channels, such as the continuous‐time Pauli channel and damped harmonic oscillators, on NISQ trapped‐ion hardware, including IonQ Harmony and Quantinuum H1‐1. Additionally, hardware‐agnostic error mitigation techniques are introduced, including Pauli channel fitting and quantum depolarizing channel inversion, to enhance the fidelity of quantum simulations. These results show strong agreement between the simulations on real quantum hardware and exact solutions, highlighting the potential of Kraus‐based methods for scalable and accurate simulation of open quantum systems on NISQ devices. This framework opens pathways for simulating more complex systems under realistic conditions in the near term.

Burdine, Colin [Department of Electrical and Compu↗
DOE OSTI2020

Using AI Simulations to Dynamically Model Multi-agent Multi-team Energy Systems

The complexity of energy systems is well known as they are complex and intricate systems. As a result, many extant studies have used many simplifications or generalizations that do not accurately reflect the nature of this complex system. In particular, most HVAC systems are modeled as a single unit, or several large units, rather than as a hierarchical composite (e.g., as a floor rather than as a collection of disparate rooms). The net result of this is that the simulations are too generic to perform meaningful analysis, machine learning, or integrated simulation. We propose using a multi-agent multi-team strategic simulations framework called SiMAMT to better define, model, simulate, and learn the HVAC environment. SiMAMT allows us to create distinct models for each type of room, hierarchically aggregate them into units (like floors, or sections), and then into larger sets (like buildings or a campus), and then perform a simulation that interacts with each sub-element individually, the teams of sub-elements collectively, and the entire set in aggregation. Further, and most importantly, we additionally model another ‘team’ within the simulation framework - the users of the systems. Again, each individual is modeled distinctly, aggregated into sub-sets, then collected into large sets. Each user, or agent, is performing on their own but with respect to the larger team goals. This provides a simulation that has a much higher model fidelity and more applicable results that match the real-world.

Franklin, D. Michael↗
DOE OSTI2019

The Current State of High-Fidelity Simulations for Main Gas Path Turbomachinery Components and Their Industrial Impact

High-fidelity simulations have become feasible for most main gas path turbomachinery components, over the past two decades. This paper introduces the key challenges of simulating and modelling turbomachinery flows and presents an overview of possible simulation strategies. A comprehensive overview is given of which particular design challenges have to date been addressed by high-fidelity simulations, with a particular focus on high-pressure and centrifugal compressors, and high-pressure and low-pressure turbines. Recommendations are provided for how quality and accuracy can be ensured for high-fidelity simulations, using direct numerical simulations of a low-pressure turbine as a case study. It is argued that industrial impact from high-fidelity simulations can be achieved in two ways, either by conducting design-of-experiment-like studies that can provide designers with insight into certain physical mechanisms and phenomena, or by helping mature and improve lower-order models. The latter is discussed with particular emphasis on recent advances in machine learning for model assessment and improvement, and the potential of one selected data-driven approach is demonstrated on predictions of wake mixing for low-pressure and high-pressure turbines.

Mechanics↗
DOE OSTI2023

Neutrino transport in general relativistic neutron star merger simulations

Abstract Numerical simulations of neutron star–neutron star and neutron star–black hole binaries play an important role in our ability to model gravitational-wave and electromagnetic signals powered by these systems. These simulations have to take into account a wide range of physical processes including general relativity, magnetohydrodynamics, and neutrino radiation transport. The latter is particularly important in order to understand the properties of the matter ejected by many mergers, the optical/infrared signals powered by nuclear reactions in the ejecta, and the contribution of that ejecta to astrophysical nucleosynthesis. However, accurate evolutions of the neutrino transport equations that include all relevant physical processes remain beyond our current reach. In this review, I will discuss the current state of neutrino modeling in general relativistic simulations of neutron star mergers and of their post-merger remnants. I will focus on the three main types of algorithms used in simulations so far: leakage, moments, and Monte-Carlo scheme. I will review the advantages and limitations of each scheme, as well as the various neutrino–matter interactions that should be included in simulations. We will see that the quality of the treatment of neutrinos in merger simulations has greatly increased over the last decade, but also that many potentially important interactions remain difficult to take into account in simulations (pair annihilation, oscillations, inelastic scattering).

Foucart, Francois (ORCID:0000000346174738)↗
DOE OSTI2024

Numerical simulation of involute-plate research reactor flow behavior using RANS, LES and DNS

This paper investigates the flow behavior of involute-plate research reactors by performing Reynolds-Averaged Navier Stokes simulation (RANS), Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) of the channel flow between fuel plates. By modeling turbulence with different numerical approaches, this study provides data with three levels of fidelity. For the RANS simulation, three widely used turbulence models, i.e., k-ε, k-ω, Reynolds Stress Turbulence model (RST) are applied by using the commercial CFD code STAR-CCM +. For LES and DNS, the open-source CFD code, Nek5000, is used given its outstanding scalability on High Performance Computer (HPC) and high-order technique. The results from RANS simulations are compared with that from LES and DNS for benchmarking. Both macroscale parameters and turbulence statistics, such as velocity magnitude, lateral velocity and turbulence kinetic energy, are presented and analyzed. The results from RANS simulation achieve good agreement with LES and DNS on velocity and turbulence kinetic energy prediction. The RST turbulence model predicts the most similar flow pattern of lateral velocity as compared to LES and DNS. The Lambda-2 (λ2) criterion with a reasonable threshold is used to demonstrate the instantaneous vortices distribution in the involute channel from both LES and DNS calculation. The DNS simulation captures more detailed turbulence especially near the corner, which explains the discrepancy between LES and DNS results near the corner. The normalized RMS error are defined and calculated to assess the performance of those turbulence models. The RST model captures the anisotropic feature of turbulence, which enable it to outperform other turbulence models for predicting the flow behavior in an involute channel. Although some discrepancies are found between LES and DNS results in the corner, the overall deviations between LES and DNS are found to be small. In conclusion, given that the computational cost of DNS calculation is an order of magnitude higher, using LES data for benchmarking RANS model is a cost-effective approach.

DNS↗
DOE OSTI2022

Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗
DOE OSTI2014

An automated target species selection method for dynamic adaptive chemistry simulations

The relative importance index (RII) approach for determining appropriate target species for dynamic adaptive chemistry (DAC) simulations using the directed relation graph with error propagation (DRGEP) method is developed. The adequacy and effectiveness of this RII method is validated for two fuels: n-heptane and isopentanol, representatives of a ground transportation fuel component and bio-alcohol, respectively. The conventional method of DRGEP target species selection involves picking an unchanging (static) set of target species based on the combustion processes of interest; however, these static target species may not remain important throughout the entire combustion simulation, adversely affecting the accuracy of the method. In particular, this behavior may significantly reduce the accuracy of the DRGEP-based DAC approach in complex multidimensional simulations where the encountered combustion conditions cannot be known a priori with high certainty. Moreover, testing multiple sets of static target species to ensure the accuracy of the method is generally computationally prohibitive. Instead, the RII method determines appropriate DRGEP target species solely from the local thermo-chemical state of the simulation, ensuring that accuracy will be maintained. Further, the RII method reduces the expertise required of users to select DRGEP target species sets appropriate to the combustion phenomena under consideration. Constant volume autoignition simulations run over a wide range of initial conditions using detailed reaction mechanisms for n-heptane and isopentanol show that the RII method is able to maintain accuracy even when traditional static target species sets fail, and are even more accurate than expert-selected target species sets. Additionally, the accuracy and efficiency of the RII method are compared to those of static target species sets in single-cell engine simulations under homogeneous charge compression ignition conditions. For simulations using more stringent DRGEP thresholds, the RII method performs similarly to that of the static target species sets. With a larger DRGEP threshold, the RII method is significantly more accurate than the static target species sets without imposing significant computational overhead. Moreover, the applicability of the RII method to a DRG-based DAC scheme is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A simulation approach to estimate energy savings potential of occupant behavior measures

Occupant behavior in buildings is a leading factor influencing energy use in buildings. Low-cost behavioral solutions have demonstrated significant potential energy savings. Estimating the behavioral savings potential is important for a more effective design of behavior change interventions, which in turn will support more effective energy-efficiency policies. This study introduces a simulation approach to estimate the energy savings potential of occupant behavior measures. First it defines five typical occupant behavior measures in office buildings, then simulates and analyzes their individual and integrated impact on energy use in buildings. The energy performance of the five behavior measures was evaluated using EnergyPlus simulation for a real office building across four typical U.S. climates and two vintages. The Occupancy Simulator was used to simulate the occupant movement in each zone with inputs from the site survey of the case building. Based on the simulation results, the occupant behavior measures can achieve overall site energy savings as high as 22.9% for individual measures and up to 41.0% for integrated measures. Although energy savings of behavior measures would vary depending upon many factors, the presented simulation approach is robust and can be adopted for other studies aiming to quantify occupant behavior impact on building performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗
DOE OSTI2017

Enabling co-simulation of tokamak plant models and plasma control systems

A system for connecting the Plasma Control System and a model of the tokamak Plant in closed loop co-simulation for plasma control development has been in routine use at DIII-D for more than 20 years and at other fusion labs that use variants of the DIII-D PCS for approximately the last decade. Here, co-simulation refers to the simultaneous execution of two independent codes with the exchange of data - Plant actuator commands and tokamak diagnostic data - between them during execution. Interest in this type of PCS-Plant simulation technology has also been growing recently at other fusion facilities. In fact, use of such closed loop control simulations is assumed to play an even larger role in the development of both the ITER Plasma Control System (PCS) and the experimental operation of the ITER device, where they will be used to support verification/validation of the PCS and also for ITER pulse schedule development and validation. We describe the key use cases that motivate the co-simulation capability and the features that must be provided by the Plasma Control System to support it. These features could be provided by the PCS itself or by a model of the PCS. If the PCS itself is chosen to provide them, there are requirements imposed on its architecture. If a PCS model is chosen, there are requirements imposed on the initial implementation of this simulation as well as long-term consequences for its continued development and maintenance. We describe these issues for each use case and discuss the relative merits of the two choices. Several examples are given illustrating uses of the co-simulation method to address problems of plasma control during the operation of DIII-D and of other devices that use the DIII-D PCS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Toward Online Adaptive Hyperthermia Treatment Planning: Correlation Between Measured and Simulated Specific Absorption Rate Changes Caused by Phase Steering in Patients

Purpose: Hyperthermia is the clinical application of heat, in which tumor temperatures are raised to 40°C to 45°C. This proven radiation and chemosensitizer significantly improves clinical outcome for several tumor sites. Earlier studies of the use of pre-treatment planning for hyperthermia showed good qualitative but disappointing quantitative reliability. The purpose of this study was to investigate whether hyperthermia treatment planning (HTP) can be used more reliably for online adaptive treatment planning during locoregional hyperthermia treatments. Methods and Materials: This study included 78 treatment sessions for 15 patients with non-muscle-invasive bladder cancer. At the start of treatments, temperature rise measurements were performed with 3 different antenna settings optimized for each patient, from which the absorbed power (specific absorption rate [SAR]) was derived. HTP was performed based on a computed tomography (CT) scan in treatment position with the bladder catheter in situ. The SAR along the thermocouple tracks was extracted from the simulated SAR distributions. Correlations between measured and simulated (average) SAR values were determined. To evaluate phase steering, correlations between the changes in simulated and measured SAR values averaged over the thermocouple probe were determined for all 3 combinations of antenna settings. Results: For 42% of the individual treatment sessions, the correlation coefficient between measured and simulated SAR profiles was higher than 0.5, whereas 58% showed a weak correlation (R of <0.5). The overall correlation coefficient between measured and simulated average SAR was weak (R=0.31; P<.001). The measured and simulated changes in average SAR after adapting antenna settings correlated much better (R=0.70; P<.001). The ratio between the measured and simulated quotients of maximum and average SARs was 1.03 ± 0.26 (mean ± SD), indicating that HTP can also correctly predict the relative amplitude of SAR peaks. Conclusions: HTP can correctly predict SAR changes after adapting antenna settings during hyperthermia treatments. This allows online adaptive treatment planning, assisting the operator in determining antenna settings resulting in increased tumor temperatures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗