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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 613 records · Page 34

Dual-wavelength correlation measurements with an airborne pulsed carbon dioxide lidar system

Dual-wavelength correlation data are presented for ground-level and airborne measurements of topographic and ocean backscatter near the 9.5-micron wavelength. Data were acquired with a pulsed carbon dioxide, dual-laser, dual-wavelength lidar system. The best system performance gave a dual-wavelength uncorrelated noise component of 2.8% and 9% standard deviation for ground-based and airborne data, respectively. This sets one limit on lidar measurement accuracy with a single pulse pair.

Bufton, J. L.↗

Review of high-performance axial-flow-compressor blade-element theory

This report presents a review of current compressor blade-element theory with particular emphasis on application to the transonic high-performance compressor. A discussion of the significant parameters of total-pressure loss and deviation angle is presented, and an indication of the extent of available knowledge and the problems involved in the determination of blade-element characteristics is given. Some recent results and considerations in this pursuit and suggestions for further avenues of investigation are indicated.

Lieblein, Seymour↗

Adaptive Control for Microgravity Vibration Isolation System

Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

Yang, Bong-Jun↗

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗

Comparison of Inlet Broadband Acoustic Liner Predictions to Quiet Technology Demonstrator 3 Flight Data

Companion acoustic liner attenuation predictions and flight data representative of certification conditions are analyzed to determine the validation quality and gain an understanding of current prediction shortcomings. These comparisons are limited to the inlet broadband component of fan noise. Two prediction methods are assessed: a traditional, semiempirical model, and a computational approach with a parabolic duct propagation code coupled with a Ffowcs Williams-Hawkings solver for free-field propagation. The semiempirical method is widely used for aircraft system noise predictions, but does not explicitly account for several physical parameters important for sound attenuation. The computational approach includes these effects, but requires a significant increase in cycle time. For the three-degree-of-freedom (3DOF) liner tested, both methods have a bias error less than 0.5 dB for cutback and takeoff power settings, and a much larger 3–4 dB bias for approach power setting. The standard deviation of each method varies between 1–2 dB for different conditions. The similar performance of both approaches illustrates that, in this instance, the additional complexity of the computational approach does not provide a clear improvement over the semiempirical method. Planned improvements to the numerical grid and source assumptions may result in reevaluation of this conclusion in later work.

aircraft system noise↗

The Muon $g$-$2$ Experiment at Fermilab

A new measurement of the anomalous magnetic moment of the muon, $a_{\mu} \equiv (g-2)/2$, will be performed at the Fermi National Accelerator Laboratory with data taking beginning in 2017. The most recent measurement, performed at Brookhaven National Laboratory (BNL) and completed in 2001, shows a 3.5 standard deviation discrepancy with the standard model value of $a_\mu$. The new measurement will accumulate 21 times the BNL statistics using upgraded magnet, detector, and storage ring systems, enabling a measurement of $a_\mu$ to 140 ppb, a factor of 4 improvement in the uncertainty the previous measurement. This improvement in precision, combined with recent improvements in our understanding of the QCD contributions to the muon $g$-$2$, could provide a discrepancy from the standard model greater than 7$\sigma$ if the central value is the same as that measured by the BNL experiment, which would be a clear indication of new physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Small Scale Mixing Demonstration Batch Transfer and Sampling Performance of Simulated HLW - 12307

The ability to effectively mix, sample, certify, and deliver consistent batches of High Level Waste (HLW) feed from the Hanford Double Shell Tanks (DST) to the Waste treatment Plant (WTP) has been recognized as a significant mission risk with potential to impact mission length and the quantity of HLW glass produced. At the end of 2009 DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS), awarded a contract to EnergySolutions to design, fabricate and operate a demonstration platform called the Small Scale Mixing Demonstration (SSMD) to establish pre-transfer sampling capacity, and batch transfer performance data at two different scales. This data will be used to examine the baseline capacity for a tank mixed via rotational jet mixers to transfer consistent or bounding batches, and provide scale up information to predict full scale operational performance. This information will then in turn be used to define the baseline capacity of such a system to transfer and sample batches sent to WTP. The Small Scale Mixing Demonstration (SSMD) platform consists of 43'' and 120'' diameter clear acrylic test vessels, each equipped with two scaled jet mixer pump assemblies, and all supporting vessels, controls, services, and simulant make up facilities. All tank internals have been modeled including the air lift circulators (ALCs), the steam heating coil, and the radius between the wall and floor. The test vessels are set up to simulate the transfer of HLW out of a mixed tank, and collect a pre-transfer sample in a manner similar to the proposed baseline configuration. The collected material is submitted to an NQA-1 laboratory for chemical analysis. Previous work has been done to assess tank mixing performance at both scales. This work involved a combination of unique instruments to understand the three dimensional distribution of solids using a combination of Coriolis meter measurements, in situ chord length distribution measurements, and electro-resistive tomography. This current work utilized the same instruments to monitor simulated waste transfers. This paper will discuss some of the scaling compromises when it came to the scaled sampling system design, handling of large quantities of material for sampling, and present data for the discuss of likely behavior of the full scale DST based on scaling correlations using a scale ratio exponent (SRE) from 0.25 to 0.45 and the behavior observed in the SSMD platform. This does not establish a scaling factor for DST mixing using paired jet mixers but is an attempt to envelope the likely performance ranges in terms of certification sampling bias, certification sample root-mean-square-deviation, and bath to batch relative standard deviation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗

Modelling nanofiltration of electrolyte solutions

This review critically examines current models for nanofiltration (NF) of electrolyte solutions. We start from linear irreversible thermodynamics, we derive a basic equation set for ion transfer in terms of gradients of ion electrochemical potentials and transmembrane volume flux. These equations are extended to the case of significant differences of thermodynamic forces across the membrane (continuous version of irreversible thermodynamics) and solved in quadratures for single salts and trace ions added to single salts in the case of macroscopically-homogeneous membranes. These solutions reduce to (quasi)analytical expressions in the popular Spiegler-Kedem approximation (composition independent phenomenological coefficients), which we extend to the case of trace ions. This enables us to identify membrane properties (e.g. ion permeances, ion reflection coefficients, electrokinetic charge density) that control its performance in NF of multi-ion solutions. Further, we specify the phenomenological coefficients of irreversible thermodynamics in terms of ion partitioning, hindrance and diffusion coefficients for the model of straight cylindrical capillaries. The corresponding expressions enable assessment of the applicability of the popular nanopore model of NF. This model (based on the use of macroscopic approaches at nanoscale) leads to a number of trends that have never been observed experimentally. We also show that the use of the Born formula (frequently employed for the description of dielectric exclusion) hardly leads to meaningful values of solvent dielectric constant in membrane pores because this formula disregards the very solvent structure whose changes are supposed to bring about the reduction of dielectric permittivity in nanopores. We conclude that the effect should better be quantified in terms of ion excess solvation energies in the membrane phase. As an alternative to the nanopore description of NF, we review recent work on the development of an advanced engineering model for NF of multi ion solutions in terms of a solution-diffusionelectromigration mechanism. This model (taking into account spontaneously arising transmembrane electric fields) captures several trends observed experimentally, and the use of trace ions can provide model parameters (ion permeances in the membrane) from experiment. We also consider a recent model (ultrathin barrier layers with deviations from local electroneutrality) that may reproduce observed feed-salt concentration dependences of membrane performance in terms of concentration independent properties like excess ion solvation energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-F-T-459: ArcCHECK Machine QA : Highly Efficient Quality Assurance Tool for VMAT, SRS & SBRT Linear Accelerator Delivery

Purpose: Quality assurance (QA) of complex linear accelerators is critical and highly time consuming. ArcCHECK Machine QA tool is used to test geometric and delivery aspects of linear accelerator. In this study we evaluated the performance of this tool. Methods: Machine QA feature allows user to perform quality assurance tests using ArcCHECK phantom. Following tests were performed 1) Gantry Speed 2) Gantry Rotation 3) Gantry Angle 4)MLC/Collimator QA 5)Beam Profile Flatness & Symmetry. Data was collected on trueBEAM stX machine for 6 MV for a period of one year. The Gantry QA test allows to view errors in gantry angle, rotation & assess how accurately the gantry moves around the isocentre. The MLC/Collimator QA tool is used to analyze & locate the differences between leaf bank & jaw position of linac. The flatness & Symmetry test quantifies beam flatness & symmetry in IEC-y & x direction. The Gantry & Flatness/Symmetry test can be performed for static & dynamic delivery. Results: The Gantry speed was 3.9 deg/sec with speed maximum deviation around 0.3 deg/sec. The Gantry Isocentre for arc delivery was 0.9mm & static delivery was 0.4mm. The maximum percent positive & negative difference was found to be 1.9 % & – 0.25 % & maximum distance positive & negative diff was 0.4mm & – 0.3 mm for MLC/Collimator QA. The Flatness for Arc delivery was 1.8 % & Symmetry for Y was 0.8 % & X was 1.8 %. The Flatness for gantry 0°,270°,90° & 180° was 1.75,1.9,1.8 & 1.6% respectively & Symmetry for X & Y was 0.8,0.6% for 0°, 0.6,0.7% for 270°, 0.6,1% for 90° & 0.6,0.7% for 180°. Conclusion: ArcCHECK Machine QA is an useful tool for QA of Modern linear accelerators as it tests both geometric & delivery aspects. This is very important for VMAT, SRS & SBRT treatments.

43 PARTICLE ACCELERATORS↗

Photovoltaic system derived data for determining the solar resource and for modeling the performance of other photovoltaic systems

Using performance data from some of the millions of installed photovoltaic (PV) modules with micro-inverters may afford the opportunity to provide ground-based solar resource data critical for developing PV projects. Here, a method was developed to back-solve for the direct normal irradiance (DNI) and the diffuse horizontal irradiance (DHI) from the measured ac power of south-facing PV module/micro-inverter systems. The method was validated using one year of irradiance and PV performance measurements for five PV systems, each with a different tilt/azimuth orientation, and located in Golden, Colorado. Compared to using a measured global horizontal irradiance for PV performance model input, using the back-solved values of DNI and DHI only increased the range of mean bias deviations from measured values by 0.6% for the modeled annual averages of the global tilt irradiance and ac power for the five PV systems. Correcting for angle-of-incidence effects is an important feature of the method to prevent underestimating the solar resource and for modeling the performance of PV systems with more dissimilar PV module orientations. The results for the method were also shown more favorable than the results when using an existing power projection method for estimating the ac power.

14 SOLAR ENERGY↗

Excess Density as a Descriptor for Electrolyte Solvent Design

Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.

74 ATOMIC AND MOLECULAR PHYSICS↗

Using "AI Poincare" to analyze non-linear integrable optics

This study dives into the applicability of using automated discovery of conserved quantities in dynamical systems relevant to accelerator physics. Specifically, we explore the performance of AI Poincaré in analyzing numerical trajectory data obtained using the McMillan system of non-linear integrable optics. A comprehensive evaluation of the algorithm's performance is conducted through diverse methodologies. These include the analysis of the estimated number of conserved quantities embedded in a dataset and the deviation of interpolated points on the inferred manifold with respect to points in actually in the dataset. the investigation identifies an optimal range of perturbation distances where the underlying manifold extraction algorithm inside AI Poincaré exhibits optimal performance. Additionally, an improved neural network architecture is proposed based on the observed results. Finally, we apply the algorithm to preliminary experimental data from the Integrable Optics Test Accelerator at Fermilab to successfully infer the number of conserved quantities even in the presence of fast decoherence of the measured signal.

Osmanov, Lazare [Free U. Tbilisi]↗

NASA NDE Fracture Critical Detectable Flaw Sizes History and Methodology

NASA requires that NDE methods and inspectors demonstrate 90% Probability of Detection (POD) with 95% confidence for critical flaw sizes when inspecting fracture critical metallic components. NASA addresses the known variability of NDE inspector capability in two ways. The first, Special NDE, requires that every inspector demonstrate the required 90/95 POD, which is resource intensive. The second approach is Standard NDE for which conservative flaw sizes for different NDE methods are provided such that it is expected that most properly trained inspectors will exceed the 90/95 POD requirement. As such, individual POD demonstration testing is not required. The origin of NASA Standard NDE dates to the start of the Space Shuttle Program in the early 1970’s. In the first study to quantitatively assess NDE methods and inspectors, the performance of multiple inspectors was evaluated for different NDE methods using a large set of fatigue cracked specimens. A rudimentary POD analysis was performed to estimate the 90/95 POD flaw size for each inspector for each method. Additionally, the average and standard deviation of the 90/95 POD flaw size across the multiple inspectors was calculated to estimate the flaw size for which 95 percent of inspectors would provide the 90/95 POD capability. These estimated 90/95/95 POD flaw sizes evolved into the NASA Standard NDE flaw sizes still in use for structural analysis five decades later. The methodology for performing Standard NDE POD studies was never documented in NASA requirements. Furthermore, POD analysis methods have significantly evolved since this seminal study. Likewise, NDE methods have improved and there has been a push to reassess Standard NDE flaw sizes for existing methods, and to develop Standard NDE flaw sizes for new methods such as digital radiography. In this study, a Standard NDE POD methodology was developed and baselined using the historical data. This reanalysis of the historical data identified several deficiencies in the original test plan as well as an overall lack of conservatism in the estimated 90/95/95 POD flaw sizes. The results of this historical review and the new methodology are being incorporated into an update of NASA NDE POD requirements.

Nondestructive Evaluation↗

The impact of physical and mental tasks on pilot mental workoad

Seven instrument-rated pilots with a wide range of backgrounds and experience levels flew four different scenarios on a fixed-base simulator. The Baseline scenario was the simplest of the four and had few mental and physical tasks. An activity scenario had many physical but few mental tasks. The Planning scenario had few physical and many mental taks. A Combined scenario had high mental and physical task loads. The magnitude of each pilot's altitude and airspeed deviations was measured, subjective workload ratings were recorded, and the degree of pilot compliance with assigned memory/planning tasks was noted. Mental and physical performance was a strong function of the manual activity level, but not influenced by the mental task load. High manual task loads resulted in a large percentage of mental errors even under low mental task loads. Although all the pilots gave similar subjective ratings when the manual task load was high, subjective ratings showed greater individual differences with high mental task loads. Altitude or airspeed deviations and subjective ratings were most correlated when the total task load was very high. Although airspeed deviations, altitude deviations, and subjective workload ratings were similar for both low experience and high experience pilots, at very high total task loads, mental performance was much lower for the low experience pilots.

Berg, S. L.↗

Feasibility of using computed tomography texture analysis parameters as imaging biomarkers for predicting risk grade of gastrointestinal stromal tumors: comparison with visual inspection

Purpose: To evaluate the feasibility of using computed tomography texture analysis (CTTA) parameters for predicting malignant risk grade and mitosis index of gastrointestinal stromal tumors (GISTs), compared with visual inspection. Method and materials: CTTA was performed on portal phase CT images of 145 surgically confirmed GISTs (mean size: 42.9 ± 37.5 mm), using TexRAD software. Mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis of CTTA parameters, on spatial scaling factor (SSF), 2–6 were compared by risk grade, mitosis rate, and the presence or absence of necrosis on visual inspection. CTTA parameters were correlated with risk grade. Diagnostic performance was evaluated with receiver operating characteristic curve analysis. Enhancement pattern, necrosis, heterogeneity, calcification, growth pattern, and mucosal ulceration were subjectively evaluated by two observers. Results: Three to four parameters at different scales were significantly different according to the risk grade, mitosis rate, and the presence or absence of necrosis (p < 0.041). MPP at fine or medium scale (r = − 0.547 to − 393) and kurtosis at coarse scale (r = 0.424–0.454) correlated significantly with risk grade (p < 0.001). HG-GIST was best differentiated from LG-GIST by MPP at SSF 2 (AUC, 0.782), and kurtosis at SSF 4 (AUC, 0.779) (all p < 0.001). CT features predictive of HG-GIST were density lower than or equal to that of the erector spinae muscles on enhanced images (OR 2.1; p = 0.037; AUC, 0.59), necrosis (OR, 6.1; p < 0.001; AUC, 0.70), heterogeneity (OR, 4.3; p < 0.001; AUC, 0.67), and mucosal ulceration (OR, 3.3; p = 0.002; AUC, 0.62). Conclusion: Using TexRAD, MPP and kurtosis are feasible in predicting risk grade and mitosis index of GISTs. CTTA demonstrated meaningful accuracy in preoperative risk stratification of GISTs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ex situ metrology and data analysis for optimization of beamline performance of aspherical pre-shaped x-ray mirrors at the advanced light source

Super high quality aspherical x-ray mirrors with a residual slope error of ~100 nrad (root-mean-square) and a height error of ~1-2 nm (peak-to-valley), and even lower, are now available from a number of the most advanced vendors utilizing deterministic polishing techniques. The mirror specification for the fabrication is based on the simulations of the desired performance of the mirror in the beamline optical system and is normally given with the acceptable level of deviation of the mirror figure and finish from the desired ideal shape. For example, in the case of aspherical x-ray mirrors designed for the Advanced Light Source (ALS) QERLIN beamline, the ideal shape is defined with the beamline application (conjugate) parameters and their tolerances. Here, we first introduce an original procedure and dedicated software developed at the ALS X-Ray Optics Laboratory (XROL) for optimization of beamline performance of pre-shaped hyperbolic and elliptical mirrors. The optimization is based on results of ex situ surface slope metrology and consists in minimization of the mirror shape error by determining the conjugate parameters of the best-fit ideal shape within the specified tolerances. We describe novel optical metrology instrumentation, measuring techniques, and analytical methods used at the XROL for acquisition of surface slope data and optimization of the optic’s beamline performance. The high efficacy of the developed experimental methods and data analysis procedures is reflected in results of measurements with and performance optimization of hyperbolic and elliptical cylinder mirrors designed and fabricated for the ALS QERLIN beamline.

47 OTHER INSTRUMENTATION↗