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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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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Fatigue of extracted lead zirconate titanate multilayer actuators under unipolar high field electric cycling

Testing of large prototype lead zirconate titanate (PZT) stacks presents substantial technical challenges to electronic testing systems, so an alternative approach that uses subunits extracted from prototypes has been pursued. Extracted 10-layer and 20-layer plate specimens were subjected to an electric cycle test under an electric field of 3.0/0.0 kV/mm, 100 Hz to 10{sup 8} cycles. The effects of measurement field level and stack size (number of PZT layers) on the fatigue responses of piezoelectric and dielectric coefficients were observed. On-line monitoring permitted examination of the fatigue response of the PZT stacks. The fatigue rate (based on on-line monitoring) and the fatigue index (based on the conductance spectrum from impedance measurement or small signal measurement) were developed to quantify the fatigue status of the PZT stacks. The controlling fatigue mechanism was analyzed against the fatigue observations. The data presented can serve as input to design optimization of PZT stacks and to operation optimization in critical applications, such as piezoelectric fuel injectors in heavy-duty diesel engines.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

srMO-BO-3GP: A sequential regularized multi-objective Bayesian optimization for constrained design applications using an uncertain Pareto classifier

Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, including multi-objective, multi-fidelity, parallelization, and latent-variable modeling, have been proposed to address the limitations of the classical BO framework. In this work, we propose a novel multi-objective BO formalism, called srMO-BO-3GP, to solve multi-objective optimization problems in a sequential setting. Three different Gaussian processes (GPs) are stacked together, where each of the GPs is assigned with a different task. The first GP is used to approximate a single-objective computed from the multi-objective definition, the second GP is used to learn the unknown constraints, and the third one is used to learn the uncertain Pareto frontier. At each iteration, a multi-objective augmented Tchebycheff function is adopted to convert multi-objective to single-objective, where the regularization with a regularized ridge term is also introduced to smooth the single-objective function. Finally, we couple the third GP along with the classical BO framework to explore the convergence and diversity of the Pareto frontier by the acquisition function for exploitation and exploration. The proposed framework is demonstrated using several numerical benchmark functions, as well as a thermomechanical finite element model for flip-chip package design optimization.

42 ENGINEERING↗
DOE OSTI2025

REIMAGINING HEAT EXCHANGERS FOR NEXT GENERATION ENVIRONMENTAL SYSTEMS

Air-to-refrigerant heat exchangers (HXs) are essential components in space conditioning, refrigeration, and power systems, and recent efforts have focused on making these devices more compact, reducing refrigerant charge and lowering manufacturing costs. Historically, HX innovation has been limited by available computational resources, design tools, and manufacturing constraints. The best available technologies utilize tube-fin and micro- or macro-channel tubes with fins, which are not necessarily the optimal designs achievable with current technology. In this paper, we highlight the latest advancements in air-to-refrigerant HXs, specifically emphasizing innovations achieved through shape and topology optimization. A multi-scale design optimization approach is introduced, alongside similar methods in literature, which enable highly sophisticated shape-optimized tube designs with more than 50% reduction in size and 25% reduction in refrigerant charge, essential for A3 refrigerant charge limit compliance. The frameworks integrate traditional heat and mass transfer science with state-of-the-art machine learning, genetic algorithms, and adjoint algorithms to create novel designs. While many of these innovative designs may not be manufacturable using conventional methods, they allow us explore the boundaries of what is possible. These novel air-to-refrigerant HXs are key enablers for ultra-low-refrigerant charge heat pump and refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Optimal Portfolio Design of Distributed Energy Resources on Puerto Rico Distribution Feeders with Long Outages after Hurricane Maria

This work details a project to design reliable, resilient, and cost-effective networked microgrids considering grid constraints and resilience metrics focused on Puerto Rico distribution feeder locations with long outages after Hurricane Maria. The project consisted primarily of modeling and simulation tasks that accomplished the following objectives: 1. Selected 10 distribution feeder models in vulnerable areas. The sample feeders are geographically distributed across Puerto Rico and vary in length to capture the wide variety of feeders on the island. 2. Determined the optimal location and sizing of distributed energy resources (DERs) on the identified distribution feeders. The systems considered as part of the microgrid solutions were solar photovoltaic (PV), battery energy storage systems (BESS) and distributed fossil fuel generation (DFFG). 3. Estimated the cost-benefit of the proposed DER portfolios. 4. Provided a set of final recommendations that inform decision making on how to do targeted planning analysis for microgrids that can supply energy to critical infrastructures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

An information-matching approach to optimal experimental design and active learning

The efficacy of mathematical models heavily depends on the quality of the training data, yet collecting sufficient data is often expensive and challenging. Many modeling applications require inferring parameters only as a means to predict other quantities of interest (QoI). Because models often contain many unidentifiable (sloppy) parameters, QoIs often depend on a relatively small number of parameter combinations. Therefore, we introduce an information-matching criterion based on the Fisher information matrix to select the most informative training data from a candidate pool. This method ensures that the selected data contain sufficient information to learn only those parameters that are needed to constrain downstream QoIs. It is formulated as a convex optimization problem, making it scalable to large models and datasets. Here, we demonstrate the effectiveness of this approach across various modeling problems in diverse scientific fields, including power systems and underwater acoustics. Finally, we use information-matching as a query function within an active learning (AL) loop for materials science applications. In all these applications, we find that a relatively small set of optimal training data can provide the necessary information for achieving precise predictions. These results are encouraging for diverse future applications, particularly AL in large machine-learning models.

Materials science↗
DOE OSTI2023

DESIGN AND OPTIMIZATION OF AN ERL FOR COOLING EIC HADRON BEAMS

The baseline scheme for hadron beam cooling in the Electron Ion Collider (EIC) calls for Coherent electron Cooling (CeC) of the hadrons with non-magnetized electrons at high energy (150 MeV electrons) and additional cooling via conventional bunched beam cooling using a precooler system. The electron beam parameters for these concepts are at or beyond the current state of the art, with electron bunch charges on the order of 1 nC and average currents on the order of 100 mA and requiring an Energy Recovery Linac (ERL) to produce such beams. Using specifications provided by BNL and JLab, physicists and engineers at Xelera Research are working on a complete design of an ERL system capable of cooling EIC hadrons.

Gulliford, C.↗
DOE OSTI2017

Moderator Demonstration Facility Design and Optimization

The Spallation Neutron Source (SNS) facility at Oak Ridge National Laboratory (ORNL) is implementing a Moderator Demonstration Facility (MDF) to demonstrate the performance characteristics of advanced moderators central to the Second Target Station (STS) for SNS. The MDF will use the "spare" front-end installation within the SNS accelerator support complex – an ion source, radio-frequency quadrupole (RFQ) accelerator, and medium-energy beam transport (MEBT) chopper - to provide a 2.5 MeV proton beam of peak current 50 mA and maximum pulse length of less than 10 s at a repetition rate of no more than 60 Hz to a suitable neutron-producing target to demonstrate those aspects of moderator performance necessary to meet the goals of the STS design e ort. The accelerator beam parameters are not open to variation beyond that described above - they are fixed by the nature of the spare front-end installation (the Integrated Test Stand Facility; ITSF). Accordingly, there are some neutronic challenges in developing prototypic moderator illumination from a very non-prototypic primary neutron source; the spallation source we are attempting to mimic has an extended neutron source volume approximately 40 cm long (in the direction of the proton beam), approximately 10 cm wide (horizontally transverse to the proton beam) and approximately 5 cm high (vertically transverse to the proton beam), and an isotropic evaporation energy spectrum with mean energy above 1 MeV. In contrast, the primary neutron source available from the 7Li(p,n) reaction (the most prolific at 2.5 MeV proton energy by more than an order of magnitude) is strongly anisotropic, with an energy spectrum that is both strongly dependent on emission angle and kinematically limited to less than 700 keV, and the interaction zone between the incident protons and any target material (neutron-producing or not) is intrinsically limited to a few tens of microns. The MDF will be unique and innovative amongst the world’s moderator test facilities in that it will be intended to be very prototypic in terms of "moderator illumination" - the spatial variation of the neutron flux entering the moderator itself - as well as capable of testing so-called high-brightness moderators in a wing configuration.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Recent progress in the design of the K-DEMO divertor

The preliminary conceptual design of the Korean fusion demonstration reactor (K-DEMO) with a major radius of 6.8 m and the fusion power of 2200 MW has been studied since 2012. The overall configuration of the K-DEMO divetor system based on the ITER-like water-cooled tungsten technology is a double-null type symmetric divertor subdivided into 32 toroidal modules for the vertical maintenance. A detached divertor scenario with impurity seeding was considered as the primary approach for the power exhaust to reduce the peak heat flux lower than the engineering limit of 10 MW/m 2 . The power exhaust performance at the scrap off layer was estimated by using UEDGE-2D code, a two-dimensional fluid transport code for collisional edge plasma and neutral species like N, Ne, and Ar. Particle and heat flux on inboard and outboard divertor targets were calculated for the detached cased depending on parameters such as the impurity seeding rate, pumping rate, and the pedestal density. On the other hand, a magnetic solution like X-divertor, snowflake divertor, and super X-divertor to expand the plasma wet area was considered for K-DEMO since the detached divertor increasing a radiation fraction by impurity seeding might be able to be unstable. However, the extremely high current of poloidal coils was required more than the engineering limit, 20 MA, to form magnetic field lines for the alternative divertors. Based on the physical calculation of the edge plasma, engineering analyses were carried out to find out the thermal and structural reliability. The thermo-hydraulic analysis confirmed thermal stability, whether all comprising materials are operating within their allowable temperature windows when the case of the peak heat flux is set to 10 MW/m 2 on the outboard divertor target. The response surface optimization method derived two optimal design candidates employing two kinds of heat sink materials, respectively: the reduced activation ferritic martensitic (RAFM) steel and CuCrZr alloy. Additionally, the drawbacks and merits of the two materials were definite. The optimal design with applying RAFM steel was vulnerable to withstand thermal and mechanical loads since low thermal conductivity caused too thin thickness of the heat sink. On the other hand, the CuCrZr alloy has critical drawbacks in terms of activation and radioactive waste despite its high thermal conductivity. Meanwhile, preliminary electromagnetic (EM) analysis was carried out to estimate the EM loads caused by the abnormal behaviors of plasma since EM loads are one of the most critical external loads for designing a DEMO divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Structural design and optimization of near-ultraviolet light-emitting diodes with wide wells

The characteristics of the near-ultraviolet (NUV) light-emitting diodes (LEDs) with wide (14-nm-thick) and narrow (2-nm-thick) wells under the situations of different numbers of wells and degree of polarization are systematically investigated. The simulation results show that the Auger recombination can be efficiently suppressed with the increase of number of wells in NUV LEDs. For the LEDs with wide wells, the quantum-confined Stark effect and Shockley–Read–Hall recombination play an important role when the number of wells increases, especially when the LED is under low current injection or high degree of polarization. In order to take the advantage of using wide wells, it is proposed that the quaternary Al{sub 0.1}In{sub 0.05}Ga{sub 0.85}N barriers be used in wide-well NUV LEDs along with the use of Al{sub 0.3}Ga{sub 0.7}N/Al{sub 0.1}Ga{sub 0.9}N superlattice electron-blocking layer to mitigate the polarization effect and electron overflow. With this band-engineering structural design, the optical performance of the wide-well NUV LEDs is much better than its thin-well counterpart even under the situation of high degree of polarization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

ASCR Workshop on In Situ Data Management: Enabling Scientific Discovery from Diverse Data Sources

In January 2019, the U.S. Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions for in situ data management (ISDM). The workshop defined ISDM as the practices, capabilities, and procedures to control the organization of data and enable the coordination and communication among heterogeneous tasks, executing simultaneously in a high-performance computing system, cooperating toward a common objective. The workshop revealed two primary, interdependent motivations for processing and managing data in situ. The first motivation is that the in situ methodology enables scientific discovery from a broad range of data sources over a wide scale of computing platforms: leadership-class systems, clusters, clouds, workstations, and embedded devices at the edge. The successful development of ISDM capabilities will benefit real-time decision-making, design optimization, and data-driven scientific discovery. The second motivation is the need to decrease data volumes. ISDM can make critical contributions to managing large data volumes from computations and experiments to minimize data movement, save storage space, and boost resource efficiency, often while simultaneously increasing scientific precision. A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery across the Office of Science mission space. Applications wanting to use the in situ capabilities include those where data analysis feeds back to the simulation, decisions are made autonomously, big data or machine learning is among the tasks to be coordinated, and computations need to be completed in real time. The workshop identified six priority research directions that highlight the components and capabilities needed for ISDM to be successful for the wide variety of applications discussed: making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Comparative study of machine learning techniques for post-combustion carbon capture systems

Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the interactions between a solvent, gas, and column's packing geometry while accounting for the thermodynamics, kinetics, heat, and mass transfer effects of the absorption process. These simulations can then be used explain a column's hydrodynamic characteristics and evaluate its CO 2 -capture efficiency. However, these approaches are computationally expensive, making it difficult to evaluate numerous designs and operating conditions to improve efficiency at industrial scales. In this work, we comprehensively explore the application of statistical ML methods, convolutional neural networks (CNNs), and graph neural networks (GNNs) to aid and accelerate the scale-up and design optimization of solvent-based post-combustion CCSs. We apply these methods to CFD datasets of countercurrent flows in absorption columns with structured packings characterized by several geometric parameters. We train models to use these parameters, inlet velocity conditions, and other model-specific representations of the column to estimate key determinants of CO 2 -capture efficiency without having to simulate additional CFD datasets. We also evaluate the impact of different input types on the accuracy and generalizability of each model. We discuss the strengths and limitations of each approach to further elucidate the role of CNNs, GNNs, and other machine learning approaches for CO 2 -capture property prediction and design optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Device Architecture Simplification of Laser Pattering in High-Volume Crystalline Silicon Solar Cell Fabrication using Intensive Computation for Design and Optimization

Prices of Si based solar modules have been continuously declining in recent years. Goodrich is pointing out that a significant portion of these cost reductions have come about due to ‘economies of scale’ benefits, but there is a point of diminishing returns when trying to lower cost by simply expanding production capacity. Developing innovative high volume production technologies resulting in an increase of conversion efficiency without adding significant production cost will be necessary to continue the projected cost reductions. The Foundational Program to Advance Cell Efficiency (FPACE) is seeking to achieve this by closing the PV efficiency gap between theoretical achievable maximum conversion efficiency - 29% for c-Si - and the current typical production - 18.5% for a typical full area back contact c-Si Solar cell – while targeting a module cost of $0.50/Watt . The research conducted by SolarWorldUSA and it’s partners within the FPACE framework focused on the development of a Hybrid metal-wrap-through (MWT) and laser-ablated PERC solar cell design employing a extrusion metallization scheme to achieve >20% efficient devices. The project team was able to simulate, develop and demonstrate the technologies necessary to build p-type MWT PERC cells with extruded front contacts. Conversion efficiencies approaching 20% were demonstrated and a path for further efficiency improvements identified. A detailed cost of ownership calculation for such a device was based on a NREL cost model and is predicting a $/Watt cost below 85 cents on a 180 micron substrate.

14 SOLAR ENERGY↗
DOE OSTI2022

Improving LiNiO 2 cathode performance through particle design and optimization

We report to enable further development of Ni-rich LiNi x Mn y Co 1-x-y O 2 (NMC, x ≥ 0.9) cathodes for commercial applications, fundamental understanding of the synthesis–property–performance relationships in the LiNiO 2 (LNO) parent phase is essential. In the present study, we report synthesis approaches to produce well-formed, similar-sized single-crystal LiNiO 2 (SC-LNO) with different shapes and dominating surface facets, and reveal the dependence of cathode rate performance and cycling stability on particle morphology and surface. While octahedron-shaped SC-LNO with the (012) surface shows better rate capability and improved ability in utilizing the kinetically slow anodic process in the 3.5 V region, cubic-shaped SC-LNO with the (104) surface delivers superior cycling stability, especially upon cycling at a high upper cutoff voltage of 4.6 V. Improvement in cycling stability is correlated with reduced surface reconstruction and preferential LiF formation through the interaction with the electrolyte on the (104) surface. Our study not only demonstrates the importance of particle morphology and surface design, it also provides key insights into desirable material properties for developing future LNO-based cathode materials with better performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Leveraging visible and near-infrared spectroelectrochemistry to calibrate a robust model for Vanadium(IV/V) in varying nitric acid and temperature levels

Spectroelectrochemistry and optimal design of experiments can be used to rapidly build accurate models for species quantification and enable a greater level of process awareness. Optical spectroscopy can provide vital elemental and molecular information, but several hurdles must be overcome before it can become a widely adopted analytical method for remote analysis in the nuclear field. Analytes with varying oxidation state, acid concentration, and fluctuating temperature must be efficiently accounted for to minimize time and resources in restrictive hot cell environments. The classic one-factor-at-a-time approach is not suitable for frequent calibration/maintenance operations in this setting. Therefore, a novel alternative was developed to characterize a system containing vanadium(IV/V) (0.01–0.1 M), nitric acid (0.1–4 M), and varying temperatures (20–45 °C). Here, spectroelectrochemistry methods were used to acquire a sample set selected by optimal design of experiments. This new approach allows for the accurate analysis of vanadium and HNO 3 concentration by leveraging UV–Vis–NIR absorption spectroscopy with robust and accurate chemometric models. The top model's root mean squared error of prediction percent values were 3.47%, 4.06%, 3.40%, and 10.9% for V(IV), V(V), HNO 3 , and temperature, respectively. These models, efficiently developed using the designed approach, exhibited strong predictive accuracy for vanadium and acid with varying oxidation states and temperature using only spectrophotometry, which advances current technology for real-world hot cell applications. Additionally, Nernstian analysis of the V(IV/V) standard potential was performed using traditional absorbance methods and multivariate curve resolution (MCR). The successful tests demonstrated that MCR Nernst tests may be valuable in highly convoluted spectral systems to better understand the redox processes' behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗
DOE OSTI2025

A modeling study of ocean thermal energy conversion resource and potential environmental effects around Kailua-Kona, Hawaii

Ocean Thermal Energy Conversion (OTEC) offers a promising renewable energy solution through a heat exchange process using the temperature difference between warm surface seawater and cold deep seawater. Because accurate resource characterization is critical for the optimal design and implementation of OTEC systems, a high-resolution numerical model is employed to better characterize the OTEC resource at Kona, Hawaii. Our model provides detailed spatial and temporal variability of the thermal gradient, which is essential for assessing the viability and efficiency of OTEC systems. The model results reveal distinct patterns and dynamics not captured by existing observations or models (e.g., lower-resolution information). These findings highlight the importance of using high-resolution models for accurate predictions of thermal gradient variability, ultimately supporting more efficient and sustainable OTEC deployment. Additionally, the study investigates the impacts of mixed water discharge from OTEC plants that can cause shock to organisms living in the surface water and potentially destabilize the water column. Understanding these effects is vital for minimizing any potential negative environmental consequences and ensuring the long-term viability of OTEC operations. Further, our model improves OTEC resource characterization, which can lead to optimal design and deployment of OTEC systems. The analysis of OTEC water discharge impacts can accelerate the development of OTEC technologies, overcoming permitting/consenting challenges. These findings contribute to the broader adoption of high-resolution modeling in ocean energy resource characterization, particularly for OTEC applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation) [SWR-26-095]

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation): Multifidelity aerodynamic polar data generation for hydrofoil/tidal-turbine airfoil sections. Foilpolars ties together three pieces: *AeroSandbox supplies the baseline airfoil coordinates (UIUC database). *G2Aero parameterizes those shapes on a Grassmannian manifold (Karcher mean + PGA basis) and samples new perturbed shapes around that basis. *XFoil (panel method) and NeuralFoil (neural-network surrogate, shipped with AeroSandbox) each solve the resulting shapes for lift, drag, moment, and pressure at the swept angles of attack, Reynolds numbers, and n_crit values. Design optimization of foil shapes in a computationally efficient way requires polars data across many candidate shapes, not just a handful of baseline foils. However, high-fidelity CFD at that scale is too costly, and naive shape perturbation strays from realistic geometries. FOILPOLARS addresses this by loading baseline airfoils (via AeroSandbox) and mapping them onto a Grassmannian manifold (via G2Aero), computing a Karcher mean and principal geodesic analysis (PGA) basis. New shapes are sampled by perturbing PGA coefficients, keeping them close to the manifold of realistic foils. Each sampled shape is evaluated across a configurable sweep of angle of attack, Reynolds number, and critical amplification factor using two solvers: XFoil (panel method) and NeuralFoil (neural-network surrogate), producing a paired dataset of lift, drag, moment, pressure, convergence, and confidence, indexed alongside each shape's PGA coefficients and shared Grassmannian basis in a single xarray dataset. From this, FOILPOLARS produces convergence summaries and comparison plots per shape, Reynolds number, and n_crit. A command-line interface exposes each pipeline stage independently, supporting data-driven design, optimization, and machine-learning workflows for foils.

Sandhu, Rimple [National Laboratory of the Rockies↗
DOE OSTI2016

Low-noise heterodyne receiver for electron cyclotron emission imaging and microwave imaging reflectometry

The critical component enabling electron cyclotron emission imaging (ECEI) and microwave imaging reflectometry (MIR) to resolve 2D and 3D electron temperature and density perturbations is the heterodyne imaging array that collects and downconverts radiated emission and/or reflected signals (50–150 GHz) to an intermediate frequency (IF) band (e.g. 0.1–18 GHz) that can be transmitted by a shielded coaxial cable for further filtering and detection. New circuitry has been developed for this task, integrating gallium arsenide (GaAs) monolithic microwave integrated circuits (MMICs) mounted on a liquid crystal polymer (LCP) substrate. The improved topology significantly increases electromagnetic shielding from out-of-band interference, leads to 10× improvement in the signal-to-noise ratio, and dramatic cost savings through integration. The current design, optimized for reflectometry and edge radiometry on mid-sized tokamaks, has demonstrated >20 dB conversion gain in upper V-band (60-75 GHz). Implementation of the circuit in a multi-channel electron cyclotron emission imaging (ECEI) array will improve the diagnosis of edge-localized modes and fluctuations of the high-confinement, or H-mode, pedestal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗