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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Throughput Analytics of Cloud Networks

A network of virtual machines at cloud server sites connected over virtual IO connections is a flexible, easily deployable, and cost-effective alternative to a physical network infrastructure with dedicated servers connected over leased fiber lines. We study the throughput performance of such a cloud network by collecting measurements over Google Cloud infrastructure spanning multiple continents. To study its ideal performance and impact of packet losses, we utilize its emulation using dedicated servers and connection hardware emulation devices. We compare the measurements over the cloud network to those over its emulation on a testbed. We examine the throughput profiles of both networks as a function of the round trip time and their utilization-concavity coefficients, estimated using measurements for common TCP versions. The throughput profile's concave-convex shape and its coefficient are critical indicators of the network performance, qualitatively and quantitatively, respectively. The results indicate their overall agreement between the production cloud network and its emulation using dedicated connections, and a near optimal throughput performance of the former except for a few under-performing connections. Also, the number of parallel flows is found to be a dominant factor in optimizing the throughput across various conditions and TCP versions.

Phanekham, Derek↗
DOE OSTI2015

Durability and shielding performance of borated Ceramicrete coatings in beta and gamma radiation fields

Ceramicrete™, a chemically bonded phosphate ceramic, was developed for nuclear waste immobilization and nuclear radiation shielding. Ceramicrete products are fabricated by an acid–base reaction between magnesium oxide and mono potassium phosphate. Fillers are used to impart desired properties to the product. Ceramicrete’s tailored compositions have resulted in several commercial structural products, including corrosion- and fire-protection coatings. Their borated version, called Borobond™, has been studied for its neutron shielding capabilities and is being used in structures built for storage of nuclear materials. This investigation assesses the durability and shielding performance of borated Ceramicrete coatings when exposed to gamma and beta radiations to predict the composition needed for optimal shielding performance in a realistic nuclear radiation field. Investigations were conducted using experimental data coupled with predictive Monte Carlo computer model. The results show that it is possible to produce products for simultaneous shielding of all three types of nuclear radiations, viz., neutrons, gamma-, and beta-rays. Additionally, because sprayable Ceramicrete coatings exhibit excellent corrosionand fire-protection characteristics on steel, this research also establishes an opportunity to produce thick coatings to enhance the shielding performance of corrosion and fire protection coatings for use in high radiation environment in nuclear industry.

Borobond↗
DOE OSTI2016

A slice of an aluminum particle: Examining grains, strain and reactivity

The Combustion Institute Micron-scale aluminum (Al) particles are plagued by incomplete combustion that inhibits their reactivity. One approach to improving reactivity is to anneal Al particles to increase dilatational (volumetric) strain which has also been linked to increased combustion performance. While optimal annealing temperatures have been identified (roughly 300 °C), little is known about cooling rate effects on particle combustion performance. This study examines the effect of quenching after annealing Al microparticles to 100, 200 and 300 °C on intra-particle dilatational strain and reactivity. Synchrotron X-ray diffraction analysis of the particles reveals the cooling rates in the range from 0.007 to 0.38 K/s have little effect on the dilatational strain of the aluminum-core, alumina-shell particles. The annealed and quenched Al particles were then combined with a metal oxidizer (copper oxide) to examine reactivity. Flame propagation experiments follow the same trend: flame speeds are unchanged until a critical annealing temperature of 300 °C is reached and performance is maintained for each annealing temperature regardless of cooling rate. These results show that altering the mechanical properties and combustion performance of Al particles is strongly dependent on the annealing temperature and unchanged with variation in cooling rate. The contributions from elastic and plastic deformation mechanisms on strain are also considered and additional experimental results are shown on the microstructure of an Al particle. Focused ion beam milling of an Al particle to electron transparency was combined with transmission electron microscope imaging in order to examine the microstructure of the Al particles. This confirmed that the Al microparticles have a polycrystalline structure shown by grains all exceeding 100 nm in size.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Response Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging

Automated spraying devices have become ubiquitous in laboratories employing matrixassisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time consuming and can lead to overall non-optimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirtytwo combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 Tesla Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal de-localization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other MALDI-MSI applications, tissue types, and matrix application approaches.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Structured for success: conjugated polymer binders with tailored composition and architecture for lithium-ion batteries

Conjugated polymer binders are replacing conventional binders in lithium-ion batteries. Herein, we examine how molecular engineering and hierarchical nanostructuring govern binder functionality and electrochemical performance. Lithium-ion batteries (LIBs) are the leading energy storage technology, yet enhancing their energy density and cycle life remains critical. Significant progress has been made in high-capacity anodes and high-voltage cathodes, but their performance is hindered by electrode degradation, where it is related to the behaviors of binders at the surface and interface. Conventional non-conductive binders like poly(vinylidene difluoride) (PVDF), combined with conductive additives, often fail to maintain electrical pathways under repeated volume changes. Alternatively, conjugated polymer binders have emerged as a superior alternative, simultaneously offering intrinsic conductivity, mechanical flexibility, and strong adhesion through π-conjugated backbones and functional groups. Their tunable molecular structure enables efficient electron/ion transport while mitigating electrode cracking. Additionally, the development of hierarchically ordered nanostructures in conjugated polymer binder can further enhance their electrochemical performance. This review examines the design principles of conjugated polymer binders, focusing on molecular engineering and nanostructural control to optimize their performance in high-loading electrodes, such as silicon-based anodes. By addressing key challenges in binder functionality, these advanced materials pave the way for next-generation high-energy-density LIBs.

Jin, Xiuyu↗
DOE OSTI2014

Modeling and simulation of a beam emission spectroscopy diagnostic for the ITER prototype neutral beam injector

A test facility for the development of the neutral beam injection system for ITER is under construction at Consorzio RFX. It will host two experiments: SPIDER, a 100 keV H{sup −}/D{sup −} ion RF source, and MITICA, a prototype of the full performance ITER injector (1 MV, 17 MW beam). A set of diagnostics will monitor the operation and allow to optimize the performance of the two prototypes. In particular, beam emission spectroscopy will measure the uniformity and the divergence of the fast particles beam exiting the ion source and travelling through the beam line components. This type of measurement is based on the collection of the H{sub α}/D{sub α} emission resulting from the interaction of the energetic particles with the background gas. A numerical model has been developed to simulate the spectrum of the collected emissions in order to design this diagnostic and to study its performance. The paper describes the model at the base of the simulations and presents the modeled H{sub α} spectra in the case of MITICA experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Utility-Scale Shared Energy Storage Deployment: Challenges, Research Gaps, and Opportunities

Although community energy storage (CES) and behind-the-meter (BTM) energy storage systems have been widely used to offer homeowners and communities a variety of localized benefits, their scalability and grid support functionalities are limited. On the other hand, utility-scale shared energy storage (USES) systems may offer a number of benefits for grid integration, scalability, and economic viability. When compared to BTM and CES alternatives, these large-scale systems provide more storage capacity, more efficient operations, and more economically viable options. The deployment of USES presents opportunities for optimizing grid performance, integrating renewable energy resources, and improving energy security at the community level. However, significant research gaps exist in optimizing the integration and operation of these systems, especially to allocate energy for consumer use, grid services, and enhancing energy resilience. This paper reviews the literature in this regard, focusing on the opportunities, research gaps, and challenges associated with USES deployment. Firstly, the paper provides an overview of USES systems and emphasizes their benefits. Secondly, the key challenges are identified, and research gaps associated with the operation and integration of these systems are highlighted. Lastly, some potential solutions and opportunities that can be adopted to facilitate the rapid deployment and management of USES are presented. Technological, economic, regulatory, and environmental aspects are also discussed in this paper, providing an overview of the current state and future prospects of this technology.

Gautam, Mukesh [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2014

SU-E-J-52: Dosimetric Benefit of Adaptive Re-Planning in Lung Cancer Stereotactic Body Radiotherapy (SBRT)

Purpose: To investigate the dosimetric benefit of adaptive re-planning for lung stereotactic body radiotherapy(SBRT). Methods: Five lung cancer patients with SBRT treatment were retrospectively investigated. Our in-house supercomputing online re-planning environment (SCORE) was used to realize the re-planning process. First a deformable image registration was carried out to transfer contours from treatment planning CT to each treatment CBCT. Then an automatic re-planning using original plan DVH guided fluence-map optimization is performed to get a new plan for the up-to-date patient geometry. We compared the re-optimized plan to the original plan projected on the up-to-date patient geometry in critical dosimetric parameters, such as PTV coverage, spinal cord maximum and volumetric constraint dose, esophagus maximum and volumetric constraint dose. Results: The average volume of PTV covered by prescription dose for all patients was improved by 7.56% after the adaptive re-planning. The volume of the spinal cord receiving 14.5Gy and 23Gy (V14.5, V23) decreased by 1.48% and 0.68%, respectively. For the esophagus, the volume receiving 19.5Gy (V19.5) reduced by 1.37%. Meanwhile, the maximum dose dropped off by 2.87% for spinal cord and 4.80% for esophagus. Conclusion: Our experimental results demonstrate that adaptive re-planning for lung SBRT has the potential to minimize the dosimetric effect of inter-fraction deformation and thus improve target coverage while reducing the risk of toxicity to nearby normal tissues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-H-BRC-02: Biological Dose Escalation for Liver SBRT Through Spatiotemporal Fractionation

Purpose: Stereotactic body radiotherapy (SBRT) has become an established treatment option for liver cancer. For patients with large tumors, the prescription dose is often limited by constraints on the mean liver dose, leading to tumor recurrence. In this work, we demonstrate that spatiotemporal fractionation schemes, ie delivering distinct dose distributions in different fractions, may allow for a 10% increase in biologically effective dose (BED) in the tumor compared to current practice where each fraction delivers the same dose distribution. Methods: We consider rotation therapy delivered with x-ray beams. Treatment plan optimization is performed using objective functions evaluated for the cumulative BED delivered at the end of treatment. This allows for simultaneously optimizing multiple distinct treatment plans for different fractions. Results: The treatment that optimally exploits fractionation effects is designed such that each fraction delivers a similar dose bath to the uninvolved liver while delivering high single fraction doses to complementary parts of the target volume. Thereby, partial hypofractionation in the tumor is achieved along with near uniform fractionation in the surrounding liver - leading to an improvement in the therapeutic ratio. The benefit of such spatiotemporal fractionation schemes depends on tumor geometry and location as well as the number of fractions. For 5-fraction treatments (allowing for 5 distinct dose distributions) an improvement in the order of 10% is observed. Conclusion: Delivering distinct dose distributions in different fractions, purely motivated by fractionation effects rather than geometric changes, may improve the therapeutic ratio. For treatment sites where the prescriptions dose is limited by mean dose constraints in the surrounding organ, such as liver cancer, this approach may facilitate biological dose escalation and improved cure rates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Bio-Based Polyurethane Materials: Technical, Environmental, and Economic Insights

Polyurethane (PU) is widely used due to its attractive properties, but the shift to a low-carbon economy necessitates alternative, renewable feedstocks for its production. This review examines the synthesis, properties, and sustainability of bio-based PU materials, focusing on renewable resources such as lignin, vegetable oils, and polysaccharides. It discusses recent advances in bio-based polyols, their incorporation into PU formulations, and the use of bio-fillers like chitin and nanocellulose to improve mechanical, thermal, and biocompatibility properties. Despite promising material performance, challenges related to large-scale production, economic feasibility, and recycling technologies are highlighted. The paper also reviews life cycle assessment (LCA) studies, revealing the complex and context-dependent environmental benefits of bio-based PU materials. These studies indicate that while bio-based PU materials generally reduce greenhouse gas emissions and non-renewable energy use, their environmental performance varies depending on feedstock and formulation. The paper identifies key areas for future research, including improving biorefinery processes, optimizing crosslinker performance, and advancing recycling methods to unlock the full environmental and economic potential of bio-based PU in commercial applications.

Jayalath, Piumi↗
DOE OSTI2018

High-Performance Molecular Dynamics Simulation for Biological and Materials Sciences: Challenges of Performance Portability, Dallas, TX, November 2018.

Highly-optimized parallel molecular dynamics programs have allowed researchers to achieve ground-breaking results in biological and materials sciences. This type of performance has come at the expense of portability: a significant effort is required for performance optimization on each new architecture. Using a metric that emphasizes speedup, we assess key accelerating programming components of four different best-performing molecular dynamics programs - GROMACS, NAMD, LAMMPS and CP2K-- each having a particular scope of application, for contribution to performance and for portability. We use builds with and without these components, tested on HPC systems. We also analyze the code-bases to determine compliance with portability recommendations. We find that for all four programs, the contributions of the non-portable components to speed are essential to the programs' performances; without them we see a reduction in time-to-solution of a magnitude that is insufferable to domain scientists. This characterizes the performance efficiency that must be approached for good performance portability on a programmatic level, suggesting solutions to this difficult problem, which should come from developers, industry and funding institutions, and possibly new research in programming languages.

Computer Science↗
DOE OSTI2013

YAPPA: a Compiler-Based Parallelization Framework for Irregular Applications on MPSoCs

Modern embedded systems include hundreds of cores. Because of the difficulty in providing a fast, coherent memory architecture, these systems usually rely on non-coherent, non-uniform memory architectures with private memories for each core. However, programming these systems poses significant challenges. The developer must extract large amounts of parallelism, while orchestrating communication among cores to optimize application performance. These issues become even more significant with irregular applications, which present data sets difficult to partition, unpredictable memory accesses, unbalanced control flow and fine grained communication. Hand-optimizing every single aspect is hard and time-consuming, and it often does not lead to the expected performance. There is a growing gap between such complex and highly-parallel architectures and the high level languages used to describe the specification, which were designed for simpler systems and do not consider these new issues. In this paper we introduce YAPPA (Yet Another Parallel Programming Approach), a compilation framework for the automatic parallelization of irregular applications on modern MPSoCs based on LLVM. We start by considering an efficient parallel programming approach for irregular applications on distributed memory systems. We then propose a set of transformations that can reduce the development and optimization effort. The results of our initial prototype confirm the correctness of the proposed approach.

Irregular applications↗
DOE OSTI2016

TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy

Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, the fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Optimizing hierarchical membrane/catalyst systems for oxidative coupling of methane using additive manufacturing

The advantage of a membrane/catalyst system in oxidative coupling of methane (OCM) compared to conventional reactive systems is that by introducing oxygen to the OCM catalytic sites through a membrane, parasitic gas phase reactions of O 2 (g), responsible for lowering product selectivity, can be avoided. The design and fabrication of membrane/catalyst systems has, however, been hampered by low volumetric chemical conversion rates, high capital cost, and difficulties in codesigning membrane and catalyst properties to optimize the performance. We solve these issues by developing a dual-layer additive manufacturing process, based on phase inversion, to design, fabricate and optimize a hollow fiber membrane/catalyst system for OCM. We demonstrate the approach though a case study using BaCe 0.8 Gd 0.2 O 3-δ (BCG) as the basis of both the catalyst and separation layers. We show that by using the manufacturing approach we can codesign the membrane thickness and catalyst surface area so that the flux of oxygen transport through the membrane and methane activation rates in the catalyst layer match each other. Here, we demonstrate that this “rate matching” is critical for maximizing the performance, with the membrane/catalyst system significantly overperforming conventional reactor designs under identical conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Optical Performance Prediction of Hyperlight Energy Collector With a New Optimized Secondary Reflector

This paper assesses the optical performance of a new linear Fresnel collector by Hyperlight Energy. It uses water as construction material to carry mini-size reflectors to save the cost. The secondary reflector adopts an optimal profile derived through a new adaptive optimization method by NREL. The optical performance of the optimal secondary reflector profile is also calculated at varying incidence angles. The results show that the secondary reflector profile possesses a constantly high performance over a wide range of incidence angle and exhibits its robustness.

Zhu, Guangdong↗
DOE OSTI2022

Development and assessment of prognosis digital twin in a NAMAC system

The nearly autonomous management and control (NAMAC) system is a comprehensive control system to assist plant operations by furnishing control recommendations to operators. Prognosis digital twin (DT-P) is a critical component in NAMAC for predicting action effects and supporting NAMAC decision-making during normal and accident scenarios. To quantifying and reducing uncertainty of machine-learning-based DT-Ps in multi-step predictions, this work investigates and derives insights from the application of three techniques for optimizing the performance of DT-P by long short-term memory recurrent neural networks, including manual search, sequential model-based optimization, and physics-guided machine learning. Finally, sequential model-based optimization and physics-guide machine learning result in smallest errors when the predicting transients are similar to the training data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗