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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

TRIO: Burst Buffer Based I/O Orchestration

The growing computing power on leadership HPC systems is often accompanied by ever-escalating failure rates. Checkpointing is a common defensive mechanism used by scientific applications for failure recovery. However, directly writing the large and bursty checkpointing dataset to parallel filesystem can incur significant I/O contention on storage servers. Such contention in turn degrades the raw bandwidth utilization of storage servers and prolongs the average job I/O time of concurrent applications. Recently burst buffer has been proposed as an intermediate layer to absorb the bursty I/O traffic from compute nodes to storage backend. But an I/O orchestration mechanism is still desired to efficiently move checkpointing data from bursty buffers to storage backend. In this paper, we propose a burst buffer based I/O orchestration framework, named TRIO, to intercept and reshape the bursty writes for better sequential write traffic to storage severs. Meanwhile, TRIO coordinates the flushing orders among concurrent burst buffers to alleviate the contention on storage server bandwidth. Our experimental results reveal that TRIO can deliver 30.5% higher bandwidth and reduce the average job I/O time by 37% on average for data-intensive applications in various checkpointing scenarios.

Wang, Teng↗
DOE OSTI2019

PERFORMANCE CHARACTERISTICS OF A VECTOR SENSOR ARRAY IN AN ENERGETIC TIDAL CHANNEL

A compact three-dimensional vector sensor array (termed the NoiseSpotter) was recently developed with the goal of characterizing and localizing sources of sound in energetic environments such as those where marine renewable energy devices are likely to be located. The three vector sensors on the NoiseSpotter are mounted on a bottom platform with each sensor suspended inside an optional flow noise removal shield. The multiple pressure and particle velocity channels on the NoiseSpotter are simultaneously sampled and stored on-board to enable coherent array processing of vector sensor array data. A series of field trials were conducted where the NoiseSpotter was deployed on a bottom platform in an 8 m deep tidal channel in Sequim Bay, Washington. Pure tones were transmitted from a drifting vessel whose distance from the bottom platform varied between 50 m and 500 m. The effect of flow noise on vector sensor array performance is quantified along with the detectability of low intensity sound in an energetic environment. Flow noise removal efficiency for each channel of every vector sensor is demonstrated using multiple metrics derived from the active and reactive intensities computed using the pressure-velocity cross-spectral density matrix. A flow noise removal shield is shown to improve the detectability of low intensity sound such as those that are expected to be emitted by marine renewable energy devices.

Raghukumar, Kaustubha↗
DOE OSTI2022

An Online Dynamic Amplitude-Correcting Gradient Estimation Technique to Align X-ray Focusing Optics

High-brightness X-ray pulses, as generated at synchrotrons and X-ray free electron lasers (XFELs), are used in a variety of scientific experiments. At these facilities, measurements often require optical equipment, e.g Compound Refractive Lenses (CRLs) to be precisely aligned and focused. The lateral alignment of CRLs to a beamline requires precise positioning along four axes: two translational, and the two rotational. At a synchrotron, alignment is often accomplished manually. However, XFEL beamlines present a beam brightness that fluctuates stochastically, making manual alignment a time-consuming endeavor. Automation using simplex or classic stochastic descent often fails, given the errant gradient estimates. Herein we present a dynamic-amplitude correction to the usual gradient based on the combination of a generalized finite difference stencil and a time-dependent sampling pattern. Intensity is recorded periodically, then used to normalize numerical derivatives against fluctuations. Error expectation is analyzed, and efficacy is demonstrated on classic benchmarks. We provide a proof of concept by laterally aligning optics on a simulated XFEL beamline using data recorded at both synchrotron and XFEL facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Assessment of Proton Deflectometry for Exploding Wire Experiments

This project provides the first demonstration of the application of proton deflectometry for the diagnosis of electromagnetic field topology and current-carrying regions in Z-pinch plasma experiments. Over the course of this project several milestones were achieved. High-energy proton beam generation was demonstrated on the short-pulse high-intensity Leopard laser, (10 Joules in ~350 femtoseconds, and the proton beam generation was shown to be reproducible. Next, protons were used to probe the electromagnetic field structure of short circuit loads in order to benchmark the two numerical codes, the resistive-magnetohydrodynamics (MHD) code, Gorgon, and the hybrid particle-in-cell code, LSP for the interpretation of results. Lastly, the proton deflectometry technique was used to map the magnetic field structure of pulsed-power-driven plasma loads including wires and supersonic jets formed with metallic foils. Good agreement between the modeling and experiments has been obtained. The demonstrated technique holds great promise to significantly improve the understanding of current flow and electromagnetic field topology in pulsed power driven high energy density plasmas. Proton probing with a high intensity laser was for the first time implemented in the presence of the harsh debris and x-ray producing z-pinch environment driven by a mega-ampere-scale pulsed-power machine. The intellectual merit of the program was that it investigated strongly driven MHD systems and the influence of magnetic field topology on plasma evolution in pulsed power driven plasmas. The experimental program involved intense field-matter interaction in the generation of the proton probe, as well as the generation of plasma subjected to 1 MegaGauss scale magnetic fields. The computational aspect included two well-documented codes, in combination for the first time to provide accurate interpretation of the experimental results. The broader impact included the support of 2 graduate students, one at UCSD and one at NTF, who were exposed to both the experimental physics work, the MHD and PIC modeling of the system. A first generation college undergraduate student was employed to assist in experiments and data analysis throughout the project. Data resulting from the research program were broadly disseminated by publication in scientific journals, and presentation at international and national conferences and workshops.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Measuring the Stress Factors for Photovoltaic (PV) Backsheet Degradation

Back sheet failure has resulted in power loss and large-scale recall of photovoltaic modules, resulting in billions of dollars in lost revenue. The light exposure on the backside of a photovoltaic module comes primarily from reflected light which alters the distribution of natural sunlight. Because of this, modelling the backside exposure and duplicating the exposure is much more difficult than modeling the frontside exposure. This project aims to study how various back sheets and junction box materials degrade under different conditions and to develop Python code to help model and predict degradation. The stress factors for back-sheet degradation must be quantified to extrapolate accelerated stress tests to the field. Test samples were placed in the A3, A4, and A5 conditions, as defined in IEC 62788-7-2, to assess the temperature and humidity dependence of ultraviolet (UV) induced degradation. We are utilizing a custom chamber with exposure from 0.5 UV-suns to 5 UV-suns to understand the dependence of degradation on light intensity. A group of samples put in the A3 condition had glass filters with 50% UV cut-offs of 320 nm, 335 nm, and 360 nm to assess the wavelength dependence of UV degradation. All this data is necessary to assess the impact of non-standard UV light exposure. The material evaluation tests include gloss measurements, attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR), UV-visible reflectance/transmittance utilizing a Cary Ci7000 spectrophotometer, and a nano-indenter for surface hardness and modulus measurements. Alongside the experimental work, there is a computational effort using raytracing and Python open-source tools in PVDeg , PVLib, and Bifacial_Radiance. This code will create specific exposure scenarios and enable the evaluation of chamber degradation relative to field degradation. Equation 1 is a strawman equation used to model degradation on the backside of a PV module. We will create simplified code, based on the results of ray-tracing calculations, which uses a view factor approach to provide fast calculations for the most common exposure scenarios.

14 SOLAR ENERGY↗
DOE OSTI2024

Stress intensity factor models using mechanics-guided decomposition and symbolic regression

The finite element method can be used to compute accurate stress intensity factors (SIFs) for cracks with complex geometries and boundary conditions. In contrast, handbook solutions act as surrogate SIF models that provide significantly faster evaluation times. However, the development of conventional surrogate SIF models relies on manual development based on low-order parameterizations. This limits surrogate model accuracy and generalizability. Here, in this paper, we develop a framework for the automated development of mechanics-guided handbook SIF solutions by using interpretable machine learning via genetic programming for symbolic regression (GPSR). Formalizing the mechanics-based approach of Raju and Newman, SIF training data is decomposed into multiple subsets. This decomposition enables parallel GPSR model development of subfunctions, each of which accounts for specific geometrical corrections with respect to a known analytical model. Using this mechanics-based approach with GPSR allows for equations to be learned with improved accuracy and reduced complexity relative to the Raju Newman equations while maintaining the inherent interpretability of mathematical expressions. In this paper, we present equations that match the complexity of the Raju Newman equations while having reduced error, as well as equations with similar errors and reduced complexity.

42 ENGINEERING↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗
DOE OSTI2018

Nuclear Resonance Vibrational Spectroscopy Definition of O 2 Intermediates in an Extradiol Dioxygenase: Correlation to Crystallography and Reactivity

The extradiol dioxygenases are a large subclass of mononuclear nonheme Fe enzymes that catalyze the oxidative cleavage of catechols distal to their OH groups. These enzymes are important in bioremediation, and there has been significant interest in understanding how they activate O 2 . The extradiol dioxygenase homoprotocatechuate 2,3-dioxygenase (HPCD) provides an opportunity to study this process, as two O 2 intermediates have been trapped and crystallographically defined using the slow substrate 4-nitrocatechol (4NC): a side-on Fe–O 2 –4NC species and a Fe–O 2 –4NC peroxy bridged species. Also with 4NC, two solution intermediates have been trapped in the H200N variant, where H200 provides a second-sphere hydrogen bond in the wild-type enzyme. While the electronic structure of these solution intermediates has been defined previously as Fe III -superoxo-catecholate and Fe III -peroxy-semiquinone, their geometric structures are unknown. Nuclear resonance vibrational spectroscopy (NRVS) is an important tool for structural definition of nonheme Fe–O 2 intermediates, as all normal modes with Fe displacement have intensity in the NRVS spectrum. In this study, NRVS is used to define the geometric structure of the H200N–4NC solution intermediates in HPCD as an end-on Fe III -superoxo-catecholate and an end-on Fe III -hydroperoxo-semiquinone. Parallel calculations are performed to define the electronic structures and protonation states of the crystallographically defined wild-type HPCD–4NC intermediates, where the side-on intermediate is found to be a Fe III -hydroperoxo-semiquinone. The assignment of this crystallographic intermediate is validated by correlation to the NRVS data through computational removal of H200. While the side-on hydroperoxo semiquinone intermediate is computationally found to be nonreactive in peroxide bridge formation, it is isoenergetic with a superoxo catecholate species that is competent in performing this reaction. In conclusion, this study provides insight into the relative reactivities of Fe III -superoxo and Fe III -hydroperoxo intermediates in nonheme Fe enzymes and into the role H200 plays in facilitating extradiol catalysis.

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

Dynamic measurements and simulations of airborne picolitre-droplet coalescence in holographic optical tweezers

We report studies of the coalescence of pairs of picolitre aerosol droplets manipulated with holographic optical tweezers, probing the shape relaxation dynamics following coalescence by simultaneously monitoring the intensity of elastic backscattered light (EBL) from the trapping laser beam (time resolution on the order of 100 ns) while recording high frame rate camera images (time resolution <10 μs). The goals of this work are to: resolve the dynamics of droplet coalescence in holographic optical traps; assign the origin of key features in the time-dependent EBL intensity; and validate the use of the EBL alone to precisely determine droplet surface tension and viscosity. For low viscosity droplets, two sequential processes are evident: binary coalescence first results from the overlap of the optical traps on the time scale of microseconds followed by the recapture of the composite droplet in an optical trap on the time scale of milliseconds. As droplet viscosity increases, the relaxation in droplet shape eventually occurs on the same time scale as recapture, resulting in a convoluted evolution of the EBL intensity that inhibits quantitative determination of the relaxation time scale. Droplet coalescence was simulated using a computational framework to validate both experimental approaches. The results indicate that time-dependent monitoring of droplet shape from the EBL intensity allows for robust determination of properties such as surface tension and viscosity. Finally, the potential of high frame rate imaging to examine the coalescence of dissimilar viscosity droplets is discussed.

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

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debye formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.

09 BIOMASS FUELS↗
DOE OSTI2016

SU-F-J-217: Accurate Dose Volume Parameters Calculation for Revealing Rectum Dose-Toxicity Effect Using Deformable Registration in Cervical Cancer Brachytherapy: A Pilot Study

Purpose: To study the feasibility of employing deformable registration methods for accurate rectum dose volume parameters calculation and their potentials in revealing rectum dose-toxicity between complication and non-complication cervical cancer patients with brachytherapy treatment. Method and Materials: Data from 60 patients treated with BT including planning images, treatment plans, and follow-up clinical exam were retrospectively collected. Among them, 12 patients complained about hematochezia were further examined with colonoscopy and scored as Grade 1–3 complication (CP). Meanwhile, another 12 non-complication (NCP) patients were selected as a reference group. To seek for potential gains in rectum toxicity prediction when fractional anatomical deformations are account for, the rectum dose volume parameters D0.1/1/2cc of the selected patients were retrospectively computed by three different approaches: the simple “worstcase scenario” (WS) addition method, an intensity-based deformable image registration (DIR) algorithm-Demons, and a more accurate, recent developed local topology preserved non-rigid point matching algorithm (TOP). Statistical significance of the differences between rectum doses of the CP group and the NCP group were tested by a two-tailed t-test and results were considered to be statistically significant if p < 0.05. Results: For the D0.1cc, no statistical differences are found between the CP and NCP group in all three methods. For the D1cc, dose difference is not detected by the WS method, however, statistical differences between the two groups are observed by both Demons and TOP, and more evident in TOP. For the D2cc, the CP and NCP cases are statistically significance of the difference for all three methods but more pronounced with TOP. Conclusion: In this study, we calculated the rectum D0.1/1/2cc by simple WS addition and two DIR methods and seek for gains in rectum toxicity prediction. The results favor the claim that accurate dose deformation and summation tend to be more sensitive in unveiling the dose-toxicity relationship. This work is supported in part by grant from VARIAN MEDICAL SYSTEMS INC, the National Natural Science Foundation of China (no 81428019 and no 81301940), the Guangdong Natural Science Foundation (2015A030313302)and the 2015 Pearl River S&T Nova Program of Guangzhou (201506010096).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Expectation-maximization algorithm for amplitude estimation of saturated optical transient signals

This paper addresses parameter estimation for an optical transient signal when the received data has been right-censored. We develop an expectation-maximization (EM) algorithm to estimate the amplitude of a Poisson intensity with a known shape in the presence of additive background counts, where the measurements are subject to saturation effects. We then compare the results of our algorithm with those of an EM algorithm that is unaware of the censoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

National Smart Manufacturing Strategic Plan: To Facilitate More Rapid Development, Deployment and Adoption of Smart Manufacturing Technologies

Smart manufacturing technologies provide real-time data and insight to improve the productivity, efficiency, and competitiveness of U.S. manufacturing, creating the potential for new jobs in the manufacturing sector. These technologies can support U.S. manufacturers’ ability to increase throughput and energy efficiency, and decrease waste, defects, and costs. A wide range of manufacturing and industrial subsectors, particularly energy-intensive and energy-dependent industries, have the potential to benefit from smart manufacturing technologies. There are technical improvements still needed to reduce the costs and barriers (trained workforce and upskilling, software-hardware integration, cost, and technical barriers to deployment of advanced sensors, computing, and communication technologies for existing manufacturing assets) to the adoption of smart manufacturing technologies, especially to small and medium-sized manufacturers, and subsequently, increase the overall adoption rate of smart manufacturing technologies. This report outlines the Department of Energy’s (DOE) strategic plan to accelerate the development and implementation of smart manufacturing technologies in the United States and the actions DOE has taken to use these technologies in smart manufacturing for the United States. DOE’s plan to facilitate more rapid development, deployment and widespread adoption of smart manufacturing technologies derive from the 2018 Strategy for American Leadership in Advanced Manufacturing. The strategy outlines a vision for America’s leadership in advanced manufacturing including the development of intelligent manufacturing systems to optimize manufacturing facilities and support the manufacturing of transformative materials. DOE’s Clean Energy Smart Manufacturing Innovation Institute (CESMII), a Manufacturing USA Institute, focuses on accelerating the development and adoption of advanced sensors, controls, platforms, and models needed for smart manufacturing. The objective is to enhance U.S. manufacturing productivity and global competitiveness through the research and development of these technologies. Smart manufacturing has the potential to improve the overall performance, energy productivity, and efficiency of manufacturing, fostering the economic competitiveness of the manufacturing sector.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

A spherical harmonic transform approach to the indexing of electron back-scattered diffraction patterns

A new approach is proposed for the indexing of electron back-scattered diffraction (EBSD) patterns. The algorithm employs a spherical master EBSD pattern and computes its cross-correlation with a back-projected experimental pattern using the spherical harmonic transform (SHT). This approach is significantly faster than the recent dictionary indexing algorithm, but shares the latter’s robustness against noise. The underlying theory is presented, followed by example applications, one on a series of Ni EBSD data sets recorded with decreasing signal-to-noise ratio, the other on a large shot-peened Al data set. The dependence of indexing speed and memory usage on the SHT bandwidth is explored. The speed gains of the new algorithm are achieved by executing real-valued Fast Fourier Transforms, explicitly incorporating crystallographic symmetry in the cross-correlation computation, and using efficient loop ordering to improve the caching behavior. The algorithm produces a cross-correlation array in the zyz Euler space; an orientation refinement procedure is proposed based on analytical derivatives of the Wigner d functions. As a result, the new approach can be applied to any diffraction modality for which the scattered intensity can be represented on a spherical surface.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Water at the graphene–substrate interface: interaction with short laser pulses

We have investigated the role of adsorption water in the local transformation of multilayer graphene deposited on an oxidised silicon substrate, which was exposed to nanosecond low-intensity focused laser radiation with a wavelength of 532 nm in the air. Experimental data obtained for a laser energy density E = 0.04 J cm{sup -2} suggest that the formation of micropits (craters) is a consequence of the multipulse removal of the layer of a water adsorbate, which is intercalated between graphene and the substrate, from the zone of laser irradiation of the graphene sheet. The energy threshold of graphene damage in the regions devoid of water was found to be higher in comparison with the initial one (0.058 against 0.048 J cm{sup -2}). According to computer simulations of the heating dynamics of the sample and the heat distribution in the substrate – adsorbate – graphene multilayer system, at energy densities corresponding to the experimental ones the water adsorbate layer heats to a temperature sufficiently high to form an increased-pressure vapour cavity under the graphene film. (interaction of laser radiation with matter)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinForms to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

High-resolution broadband spectroscopy using externally dispersed interferometry at the Hale telescope: Part 1, data analysis and results

High-resolution broadband spectroscopy at near-infrared wavelengths (950 to 2450 nm) has been performed using externally dispersed interferometry (EDI) at the Hale telescope at Mt. Palomar. Observations of stars were performed with the “TEDI” interferometer mounted within the central hole of the 200-in. primary mirror in series with the comounted TripleSpec near-infrared echelle spectrograph. These are the first multidelay EDI demonstrations on starlight, as earlier measurements used a single delay or laboratory sources. We demonstrate very high (10×) resolution boost, from original 2700 to 27,000 with current set of delays (up to 3 cm), well beyond the classical limits enforced by the slit width and detector pixel Nyquist limit. Significantly, the EDI used with multiple delays rather than a single delay as used previously yields an order of magnitude or more improvement in the stability against native spectrograph point spread function (PSF) drifts along the dispersion direction. We observe a dramatic (20×) reduction in sensitivity to PSF shift using our standard processing. A recently realized method of further reducing the PSF shift sensitivity to zero is described theoretically and demonstrated in a simple simulation which produces a 350× times reduction. We demonstrate superb rejection of fixed pattern noise due to bad detector pixels—EDI only responds to changes in pixel intensity synchronous to applied dithering. This part 1 describes data analysis, results, and instrument noise. Lastly, a section on theoretical photon limited sensitivity is in a companion paper, part 2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗