Design and analysis of nested case–control studies for recurrent events subject to a terminal event
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Mathematical & Computational Biology↗
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Human-AI Collaboration Among Engineering and Design Professionals: Three Strategies of Generative AI Use
Designers are increasingly using Generative Artificial Intelligence (GenAI) in design processes; however, knowing how designers use GenAI--especially in professional design practice--is under-explored. This paper presents an ethnographic study of a design team at NASA that explores the natural variation of GenAI use across team members during a speculative design workflow. We aimed to uncover when, how, and why GenAI tools were or were not employed using ethnographic observations to map the team's speculative design process and follow-up interviews to provide deeper insights into team members' interactions (or lackthereof) with GenAI. Through inductive qualitative coding, our analysis revealed three strategies of GenAI use observed among professional engineers and designers--intimate co-design with GenAI, selective delegation to GenAI, and minimal use of GenAI--as well as factors that appeared to influence their decisions whether or not to use GenAI. This study proposes new theory in human-AI collaboration that sheds light on the strategies, rationale, and circumstances under which design professionals use GenAI. Future work that builds upon these insights include examining a larger sample size of engineering and design professionals in uncontrolled design process experiences and exploring the impact that design tasks, goals, and constraints have on a participants decision to leverage GenAI tools.
design practice↗
Development of an In Situ Fission Gas Release Instrument for Fuel Sample Irradiations in the High Flux Isotope Reactor
Experimental measurement of gaseous fission product release with respect to temperature and burnup is a critical aspect of understanding nuclear fuel performance, validating predictive models, and qualifying new fuels. To measure this phenomenon in real-time, Oak Ridge National Laboratory has developed an instrument for measuring in situ fission gas release from small-scale fuel samples irradiated in the High Flux Isotope Reactor (HFIR). The instrument uses a continuous flow of Heover the fuel samples to sweep gaseous fission products from a sealed capsule in the HFIR Be reflector to an instrument station adjacent to the reactor. The instrument station houses two high-purity germanium (HPGe) detectors that measure decay gamma rays from fission products passing through a room temperature dwell chamber placed over the detector crystal. The sealed capsules in the reactor are designed to modulate fuel sample temperatures between 700 and 1,100°C by changing the Ar/He gas mixture surrounding the capsules during irradiation. N-type thermocouples are incorporated into the capsule housing to record real-time fuel temperatures. The capsules are heated primarily by prompt gamma rays emitted from the HFIR core with minimal heat contributions from fission in the fuel samples to minimize temperature gradients in the specimens for separate-effects characterization of the material. This paper describes modeling of time-dependent nuclear heating and fission product formation in fuel samples, thermal characteristics of the in-core capsules, and expected gaseous fission product gamma spectra at the HPGe instrument station.
Mulligan, Padhraic L [ORNL] (ORCID:000000025826540↗
Multidisciplinary concurrent optimization framework for multi-phase building design process
Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
A Multi-Disciplinary Analysis Framework for the Design of Small Launch Vehicles
Between the years of 1995 and 2014 the number of small satellites (1-500 kg) went up from 20 to 180. [1] Out of the 180 launched in 2014 66% were Nano satellites (1-10 kg). [1] With this trend of smaller satellites, one would expect a rise in number of small launch vehicles (SLVs are defined by capability to carry 1-100 kg to orbit), but this has not happened: [3] only 8% of all small satellites are launched on SLVs and the others become secondary payloads on regular launch vehicles. [1] This results in small satellites being placed into either suboptimal orbits or waiting for launch schedules to align with bigger launches, resulting in long waiting times. Dedicated SLVs could improve the responsiveness of small satellite launches, but SLV design is complicated by the large architecture space needed to be explored in order to find efficient and affordable designs. The SLV architecture trade space contains many discrete options, e.g. solid vs. liquid fuels, air launch vs. ground launch, number of stages, etc. [2][3] Performing detailed analysis for all the options at once would be prohibitive. Thus, a sizing environment/framework that is capable of providing necessary information for conceptual-level trade studies and can rapidly explore the vast SLV architecture space is necessary. The framework, illustrated in Figure 1, consists of four disciplines central to the sizing and synthesis of launch vehicles: propulsion, aerodynamics, structures, and trajectory. For the aerodynamics and trajectory disciplines, Missile DATCOM and POST2 are used, respectively. The propulsion and structures disciplines are represented in the framework with tools developed at ASDL Georgia Tech. For propulsion, the Solid Motor Analysis Code (SMAC) is a physics-based conceptual design tool for solid rocket motors. SMAC is capable of geometric burn simulation, ballistic analysis, and prediction of thrust performance. [4] For structures, Launch Vehicle Structural Analysis (LVSA) tool is a physics-based tool that focuses on structural dynamic analysis with sizing capability. These tools are integrated into the framework illustrated in Figure 1 with the corresponding connections described in Table 1. The process flow is as follows: first, SMAC sizes insulation and calculates maximum operating pressures for each vehicle stage. The MEOP and insulation thickness values from SMAC are fed to LVSA which then utilizes this information to size the motor casing. This creates a feedback loop between LVSA and SMAC that converges on the radius available for fuel, casing, and insulation thickness. Once the stage sizing is converged on SMAC creates an engine deck that is passed to POST2. Next, the data from SMAC and LVSA goes into Missile DATCOM which generates an aerodynamics database for POST2. Finally, POST2 performs a targeting optimization while maximizing the payload mass to orbit. Within the framework, POST2 is automated in order to be robust to a wide variety of possible designs by performing a Monte Carlo simulation over the initialization vector of the POST2 optimization variables. To demonstrate the capability of this framework, a sample problem of exploring the design space of an SLV capable of placing satellites into a low Earth orbit (inclination=47 deg, 196.5 by 211.3 nm) is used. This sample problem is a ground-launched SLV consisting of four in-line SRM stages. The multidisciplinary design analysis (MDA) environment is utilized to explore a design space consisting of 22 continuous and 12 discrete variables, shown by Table 1 by blocks 1,2,3. Running a full factorial design of experiments (DOE) would have been prohibitively expensive even with this reduced design space, thus a space filling design with 3,502 and then additional expansion of 2,602 cases was used. The first DOE consisted of 3,502 cases, and all of the variables were varied. These input variables are listed in blocks 1, 2, and 3 in Table 1. Most of the variables are propulsion related with stage lengths determining the delta-V split of the SLV. The expansion consisted of 2,602 cases, and the continuous variables were set to be equal to the most promising designs from the sizing of first DOE. For each set of continuous variables, the discrete variables (grain type, star points, and propellant) were to varied. The results of the DOE can be seen in Figure 2; each of the points in this plot represents a closed launch vehicle that reaches the targeted orbit. For each of the cases, there is information on flown trajectory, structural, and propulsion properties of the SLV. For example, Figure 3 shows changes in altitude and velocity with time for a particular case. The right side of Figure 3 clearly shows the coasting (slow decrease) and burning phases (sharp increase) of the SLV mission. LV mass is positively correlated with the optimized payload mass to orbit because heavier LVs carry more fuel and thus have more stored chemical energy. Furthermore, for any given payload mass to orbit, the most efficient design would result in the smallest LV. The results as visualized in Figure 2 shows this tradeoff, and the Pareto frontier of the efficient designs can be seen along the dotted line. Figure 2 can be divided into regions with the lowest mass vehicles corresponding to the minimum bound on radius, and the highest mass vehicles corresponding to the maximum bound on radius. Within a mass region, the discrete variables, such as propellant type and propellant grain arrangement, have the most effect on payload mass. This paper presents an MDA framework that can perform an automated physics-based sizing of SLV designs and a corresponding methodology to utilize the MDA to explore the design space of SLVs. The proposed methodology was applied to a perform a design space exploration for a four stage SLV. The outputs show the expected pareto frontier forming and provide detailed information about the SLV performance and staging. Using the produced data, it will be possible to select a set of pareto optimal designs that can then be further explored in subsequent design cycles. This demonstration shows that automated design space exploration should be used in the early phase design of future SLV concepts.
Nikita S Birbasov↗
Optimized, Budget-constrained Monitoring Well Placement Using DREAM
Defining the ideal suite of monitoring technologies to be deployed at a carbon capture and storage (CCS) site presents a challenge to project developers, financers, insurers, regulators and other stakeholders. The monitoring, verification, and accounting (MVA) toolkit offers a suite of technologies to monitor an extensive range of parameters across a wide span of spatial and temporal resolutions, each with their own degree of sensitivity to changes in the parameter being monitored. Understanding how best to optimize MVA budgets to minimize the time to leak detection could help to address issues around project risks, and in turn help support broad CCS deployment. This paper presents a case study demonstrating an application of the Designs for Risk Evaluation and Management (DREAM) tool using an ensemble of CO 2 leakage scenarios taken from a previous study on leakage impacts to groundwater. Impacts were assessed and monitored as a function of pH, total dissolved solids (TDS), and trace metal concentrations of arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb). Using output from the previous study, DREAM was used to optimize monitoring system designs based on variable sampling locations and parameters. The algorithm requires the user to define a finite budget to limit the number of monitoring wells and technologies deployed, and then iterates well placement and sensor type and location until it converges on the configuration with the lowest time to first detection of the leak averaged across all scenarios. To facilitate an understanding of the optimal number of sampling wells, DREAM was used to assess the marginal utility of additional sampling locations. Based on assumptions about monitoring costs and replacement costs of degraded water, the incremental cost of each additional sampling well can be compared against its marginal value in terms of avoided aquifer degradation. Applying this method, DREAM identified the most cost-effective ensemble with 14 monitoring locations. Here, while this preliminary study applied relatively simplistic cost and technology assumptions, it provides an exciting proof-of-concept for the application of DREAM to questions of cost-optimized MVA system design that are informed not only by site-specific costs and technology options, but also by reservoir simulation results developed during site characterization and operation.
47 OTHER INSTRUMENTATION↗
Urban Dispersion Virtual Workshop: Designing the Next Generation Urban Dispersion Field Programs
The overarching objective of this workshop is to start the process of planning and implementing the “Next Generation of Urban Dispersion Studies”. We have organized this program to bring people interested in this complex problem together. We have representation from different disciplines, different agencies, and different academic institutions. The workshop is organized around several questions: • What are the needs of the emergency response community and how do we design models and experiments to address them? • What model improvements do the user communities need? • How do we design tracer release and sampling to address questions temporal (e.g., diurnal and seasonal variation) and spatial (e.g., land/urban/water gradients) for the broadest applicability? • What are the next-generation measurements needed to improve the data sets? • How do we implement the next generation urban dispersion experiments? The Virtual workshop format is exciting. We view this as an experiment which, if successful, will bring a large group of people together from the community to design the next generation urban experiments. We have many agencies participating: DOE-BER, DHS, FEMA, NNSA, NARAC, DTRA, NYPD, and NIST. The registration list includes over 40 people including participants from well beyond the US including Spain and Canada.
54 ENVIRONMENTAL SCIENCES↗
Case-Based Capture and Reuse of Aerospace Design Rationale
The goal of this project is to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project applies case-based reasoning (CBR) and concept mapping (CMAP) tools to the task of capturing, organizing, and interactively accessing experiences or "cases" encapsulating the methods and rationale underlying expert aerospace design. As stipulated in the award, Indiana University and Ames personnel are collaborating on performance of research and determining the direction of research, to assure that the project focuses on high-value tasks. In the first five months of the project, we have made two visits to Ames Research Center to consult with our NASA collaborators, to learn about the advanced aerospace design tools being developed there, and to identify specific needs for intelligent design support. These meetings identified a number of task areas for applying CBR and concept mapping technology. We jointly selected a first task area to focus on: Acquiring the convergence criteria that experts use to guide the selection of useful data from a set of numerical simulations of high-lift systems. During the first funding period, we developed two software systems. First, we have adapted a CBR system developed at Indiana University into a prototype case-based reasoning shell to capture and retrieve information about design experiences, with the sample task of capturing and reusing experts' intuitive criteria for determining convergence (work conducted at Indiana University). Second, we have also adapted and refined existing concept mapping tools that will be used to clarify and capture the rationale underlying those experiences, to facilitate understanding of the expert's reasoning and guide future reuse of captured information (work conducted at the University of West Florida). The tools we have developed are designed to be the basis for a general framework for facilitating tasks within systems developed by the Advanced Design Technologies Testbed (ADTT) project at ARC. The tenets of our framework are (1) that the systems developed should leverage a designer's knowledge, rather than attempting to replace it; (2) that learning and user feedback must play a central role, so that the system can adapt to how it is used, and (3) that the learning and feedback processes must be as natural and as unobtrusive as possible. In the second funding period we will extend our current work, applying the tools to capturing higher-level design rationale.
Leake, David B.↗
Image gathering and coding for digital restoration: Information efficiency and visual quality
Image gathering and coding are commonly treated as tasks separate from each other and from the digital processing used to restore and enhance the images. The goal is to develop a method that allows us to assess quantitatively the combined performance of image gathering and coding for the digital restoration of images with high visual quality. Digital restoration is often interactive because visual quality depends on perceptual rather than mathematical considerations, and these considerations vary with the target, the application, and the observer. The approach is based on the theoretical treatment of image gathering as a communication channel (J. Opt. Soc. Am. A2, 1644(1985);5,285(1988). Initial results suggest that the practical upper limit of the information contained in the acquired image data range typically from approximately 2 to 4 binary information units (bifs) per sample, depending on the design of the image-gathering system. The associated information efficiency of the transmitted data (i.e., the ratio of information over data) ranges typically from approximately 0.3 to 0.5 bif per bit without coding to approximately 0.5 to 0.9 bif per bit with lossless predictive compression and Huffman coding. The visual quality that can be attained with interactive image restoration improves perceptibly as the available information increases to approximately 3 bifs per sample. However, the perceptual improvements that can be attained with further increases in information are very subtle and depend on the target and the desired enhancement.
Huck, Friedrich O.↗
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore’s Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to MLexperts because of lack of training data and relevant, easy-to-use workflows. Wepresent ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state. The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res2) and code(https://leap-stc.github.io/ClimSim)arereleasedopenlytosupport the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society.
artificial intelligence, machine learning↗
Low Cost Nuclear Thermal Rocket Cermet Fuel Element Environment Testing
Deep space missions with large payloads require high specific impulse (Isp) and relatively high thrust in order to achieve mission goals in reasonable time frames. Conventional, storable propellants produce average Isp. Nuclear thermal rockets (NTR) capable of high Isp thrust have been proposed. NTR employs heat produced by fission reaction to heat and therefore accelerate hydrogen which is then forced through a rocket nozzle providing thrust. Fuel element temperatures are very high (up to 3000K) and hydrogen is highly reactive with most materials at high temperatures. Data covering the effects of high temperature hydrogen exposure on fuel elements is limited. The primary concern is the mechanical failure of fuel elements which employ high-melting-point metals, ceramics or a combination (cermet) as a structural matrix into which the nuclear fuel is distributed. It is not necessary to include fissile material in test samples intended to explore high temperature hydrogen exposure of the structural support matrices. A small-scale test bed designed to heat fuel element samples via non-contact RF heating and expose samples to hydrogen is being developed to assist in optimal material and manufacturing process selection without employing fissile material. This paper details the test bed design and results of testing conducted to date.
Bradley, David E.↗
Direct Analysis of Organic Compounds in Liquid Using a Miniature Photoionization Ion Trap Mass Spectrometer with Pulsed Carrier-Gas Capillary Inlet
A miniature ion trap mass spectrometer with capillary direct sampling and vacuum ultraviolet photoionization source was developed to conduct trace analysis of organic compounds in liquids. Self-aspiration sampling is available where the samples are drawn into the vacuum chamber through a capillary with an extremely low flow rate (less than 1 μL/min), which minimizes sample consumption in each analysis to tens of micrograms. A pulsed gas-assisted inlet was designed and optimized to promote sample transmission in the tube and facilitate the cooling of ions, thereby improving instrument sensitivity. A limit of detection of 2 ppb could be achieved for 2,4-dimethylaniline in a methanol solution. The sampling system described in the present study is specifically suitable for a miniature photoionization ion trap mass spectrometer that can perform rapid and online analysis for liquid samples. .
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Determination of control-surface characteristics from NACA plain-flap and tab data
The data from previous NACA pressure-distribution investigations of plain flaps and tabs with sealed gaps have been analyzed and are presented in this paper in a form readily applicable to the problems of control-surface design. The experimentally determined variation of aerodynamic parameters with flap chord and tab chord are given in chart form and comparisons are made with the theory. With the aid of these charts and the theoretical relationships for a thin airfoil, the aerodynamic characteristics for control surfaces of any plan form with plain flaps and tabs with sealed gaps may be determined. A discussion of the basic equations of the thin-airfoil theory and the development of a number of additional equations that will be helpful in tail design are presented in the appendixes. The procedure for applying the data is described and a sample problem of horizontal tail design is included. The data presented and the method of application set forth in this report should provide a reasonably accurate and satisfactory means of computing the aerodynamic characteristics of control surfaces.
Ames, Milton B↗
Microbial Air Sampler Payload - Astrobee
The following package 2020-09-28 Microbial Air Sampler folders consist of a prototype design of a microbial air sample payload to fit in the bays of Astrobee free-flyer. There are several CAD designs prototypes and documentation about the concept and the current air sampler device.
Jose Cortez↗
Laboratory reflectometer for the investigation of optical elements in a wavelength range of 5–50 nm: description and testing results
We describe a laboratory reflectometer developed at the IPM RAS for precision measurements of spectral and angular dependences of the reflection and transmission coefficients of optical elements in a wavelength range of 5–50 nm. The radiation is monochromatised using a high-resolution Czerny–Turner spectrometer with a plane diffraction grating and two spherical collimating mirrors. A toroidal mirror focuses the probe monochromatic beam on a sample. The X-ray source is a highly ionised plasma produced in the interaction of a high-power laser beam with a solid target at an intensity of 10{sup 11}–10{sup 12} W cm{sup –2}. To stabilise the emission characteristics, the target executes translatory and rotary motions in such a way that every pulse irradiates a new spot. The short-focus lens is protected from contamination by erosion products with the use of a specially designed electromagnetic system. The samples under study are mounted on a goniometer is accommodated in a dedicated chamber, which provides five degrees of freedom for samples up to 500 mm in diameter and two degrees of freedom for a detector. The sample mass may range up to 10 kg. The X-ray radiation is recorded with a detector composed of a CsI photocathode and two microchannel plates. A similar detector monitors the probe beam intensity. The spectral reflectometer resolution is equal to 0.030 nm with the use of ruled gratings with a density of 900 lines mm{sup –1} (spectral range: 5–20 nm) and to 0.067 nm for holographic gratings with a density of 400 lines mm{sup –1} (spectral range: 10–50 nm). We analyse the contribution of higher diffraction orders to the probe signal intensity and the ways of taking it into account in the measurements. Examples are given which serve to illustrate the reflectometer application to the study of multilayer mirrors and filters. (paper)
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
The influence of sampling rate on the dynamics and control of aeronautical systems
It is shown in the design of aeronautical control systems that sampling rate variations give rise to migrations of the discrete eigenvalues for both the plant and the controllers. In general, these migrations tend to degrade simulation fidelity and the overall performance of Ultrareliable Fault Tolerant Control Systems (UFTCS). These systems consist of a redundant asynchronous network of microprocessors which use sensor information to generate the servo commands that drive actuators, thrust linkages, etc. A change in the sampling period of a single microprocessor will, in addition to causing an eigenvalue shift, alter the magnitude of the servo command issued by the controller. The influence of these changes and the effect of initial conditions and skew are considered.
Howard, J. C.↗
Application of BISON to UO 2 MiniFuel fission gas release analysis
There has been a recent push to accelerate fuel qualification by developing revolutionary capabilities to reduce irradiation periods, and thereby, reduce the time required to qualify a new fuel system. One such capability is the MiniFuel irradiation capsule designed to miniaturize fuel samples and irradiate “mini” fuel samples under isothermal temperature conditions. MiniFuel allows steady-state irradiations to decouple the traditionally coupled fission rate (i.e., power) and temperature parameters to understand and generate microstructures observed in fuel operated in a commercial reactor. Furthermore, this process offers the possibility to gather in situ data as well as postirradiation or transient data such as thermal conductivity, specific heat, fission gas diffusion and release, etc. However, accelerating fuel qualification is not solely reliant on generating large amounts of data but also on developing an informed test matrix designed to rapidly generate impactful data. Additionally, this process is reliant on fuel performance codes, such as BISON, to evaluate MiniFuel irradiations using existing material models. This process pinpoints model/data gaps, identifies desired irradiation conditions, and subsequently supports model validation and development. This work describes the use of BISON to perform a number of sensitivity studies designed to understand conditions that lead to fission gas release (FGR) under steady-state isothermal irradiation conditions and temperature transient conditions. The model is applied to a UO 2 MiniFuel example and shows an overall good qualitative agreement with experimental FGR annealing tests under different temperature conditions. It also accounts well for microstructural effects on FGR. When quantitatively compared with FGR data from previously irradiated 103 MWd/kgU UO 2 discs under thermal annealing, the model shows a less satisfactory agreement with the experimental data. Finally, a UO 2 MiniFuel test matrix is proposed to help to extend the model's operational range and validate the new FGR model capabilities to higher burnups and transient conditions.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Nanopositioning Flexure Stages Development for Synchrotron Radiation Instrumentation at the Advanced Photon Source
Nanopositioning techniques present an important capability to support the state-of-the-art synchrotron radiation instrumentation research for the Advanced Photon Source (APS) operations and upgrade project. To overcome the performance limitations of precision ball-bearing-based or roller-bearing-based stage systems, compact nanopositioning flexure stages have been designed and developed at the APS for x-ray beamline instrumentation applications. Recent progress of such stages development is discussed in this paper, which includes: rotary flexure stages with degrees travel range and 10-nrad-level resolution for x-ray monochromators and analysers, tip-tilting flexure stages for K-B mirror based nanofocusing hard x-ray optics, and linear vertical and horizontal nanopositioning flexure stages with centimeter-level travel range and microradian-level motion trajectory reproducibility for x-ray optics and sample manipulation. The mechanical design and preliminary test results are described in this paper.
Nanopositioning, X-ray optics, synchrotron radiati↗