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At least 127 records · Page 7

An Approach to V&V of Embedded Adaptive Systems

Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

Liu, Yan↗

Visualizing Flow Over Parametric Surfaces Using Line Integral Convolution

Line Integral Convolution (LIC) is a powerful technique for imaging and animating vector fields. We extend the LIC paradigm in three ways: (1) The existing technique is limited to vector fields over a regular Cartesian grid. We extend it to vector fields over parametric surfaces, such as those found in curvilinear grids, used in computational fluid dynamics simulations; (2) Periodic motion filters can be used to animate the flow visualization. When the flow lies on a parametric surface, however, the motion appears misleading. We explain why this problem arises and show how to adjust the LIC algorithm to handle it; (3) We introduce a technique to visualize vector magnitudes as well as vector direction. Cabral and Leedom have suggested a method for variable-speed animation, which is based on varying the frequency of the filter function. We develop a different technique based on kernel phase shifts which we have found to show substantially better results. Our implementation of these algorithms utilizes texture-mapping hardware to run in real time, which allows them to be included in interactive applications.

Forssell, Lisa↗

Implementation of quantum key distribution and quantum clock synchronization via time bin encoding

Quantum key distribution allows for a provably secure transmission of cryptographic keys over an optical channel. Encoded polarization states or time-bin degree of freedom have been used for successful demonstrations. However, photon losses in long fibers, slow single photon detectors, and detector dark counts significantly limit the overall bit rate. Improving key throughput and reducing the overhead of key reconciliation remain as major challenges. Methods which utilize multiple time bins allow for multiple key bits to be encoded in a single photon, thus increasing the fidelity of transmitted keys and decreasing the overhead of key reconciliation in real-world conditions. Previous implementations of these methods required that Alice and Bob share a time reference by sharing a dedicated classical channel used for synchronization. This work presents a technique that allows two parties to exchange time-bin encoded photons without the need for synchronized time references. Our technique uses a framing protocol which allows Alice to encode a time reference along with a key which is determined by Alice before transmission. Security can be achieved by monitoring the visibility of a pair of Franson interferometers, using decoy pulses and measuring the round trip time between Alice and Bob. The bit rate of this technique is limited only by the recovery time of the detector and the speed of the modulation electronics. We experimentally demonstrate a raw bit rate of 5Mb/s over an optical channel with 55dB of loss, which is competitive with current research. We also demonstrate absolute timing synchronization with an accuracy of 20ps.

encryption↗

Use of friction stir processing to synthesize nanocrystalline, grain boundary segregating Fe-Ti alloys

Grain boundary segregating alloys, a class of alloys designed such that nanocrystalline grain sizes are thermodynamically stabilized by the presence of high segregation energy solutes at the grain boundaries, are typically produced through geometrically limited processing techniques such as equal channel angular extrusion or thin film sputtering. Here, this study explores the use of friction stir processing (FSP) as a novel means of studying and producing these alloys using a test system of Fe-6at%Ti. Spot FSPs with a range of processing parameter sets were produced on bulk, coarse grained bars of material and optimal parameters were identified. Microscopy identified a range of processed materials which achieved nanocrystalline grains on the order of 100 nm, delineating a critical window of processing parameters which limit heat input while inducing sufficient plastic deformation for grain refinement. The finest grained nanocrystalline Fe-Ti achieved a hardness of 7.68 GPa, a significant increase in hardness over pure Fe with a similar microstructure due to increased dislocation density from FSP as well as several strengthening mechanisms produced through the presence and segregation of Ti. These results demonstrated the feasibility of using FSP to produce nanocrystalline grain boundary segregating alloys.

Fe alloys↗

Co-training of multiple neural networks for simultaneous optimization and training of physics-informed neural networks for composite curing

This paper introduces a Physics-Informed Neural Network (PINN) technique that co-trains neural networks (NNs) that represent each function in a system of equations to simultaneously solve equations representing an out-of-autoclave (OOA) cure process while conducting optimization in adherence to process requirements. Specifically, this co-training approach benefits from using NNs to represent OOA inputs (air temperature profile) and outputs (part and tool temperature profiles and degree of cure). Production requirements can then be levied on the inputs, such as maximum air temperature and minimum cure cycle, and simultaneously on the outputs, such as degree of cure, maximum part temperature, and part temperature rate limits. The technique is validated with finite element (FE) simulations and physical experiments for curing a Toray T830H-6 K/3900-2D composite panel. Furthermore, this novel approach efficiently models and optimizes the OOA cure process.

Composite curing↗

Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements

Quantifying chemical compositions around nanovoids is a fundamental task for research and development of various materials. Atom probe tomography (APT) and scanning transmission electron microscopy (STEM) are currently the most suitable tools because of their ability to probe materials at the nanoscale. Both techniques have limitations, particularly APT, because of insufficient understanding of void imaging. Here, we employ a correlative APT and STEM approach to investigate the APT imaging process and reveal that voids can lead to either an increase or a decrease in local atomic densities in the APT reconstruction. Simulated APT experiments demonstrate the local density variations near voids are controlled by the unique ring structures as voids open and the different evaporation fields of the surrounding atoms. We provide a general approach for quantifying chemical segregations near voids within an APT dataset, in which the composition can be directly determined with a higher accuracy than STEM-based techniques.

36 MATERIALS SCIENCE↗

Comparison of Shadowgraphy and X-Ray Phase Contrast Methods for Characterizing a DT Ice Layer in an Inertial Confinement Fusion Target

Shadowgraphy and x-ray phase contrast (XPC) imaging are two techniques that are used for characterizing the deuterium-tritium ice layer in Inertial Confinement Fusion targets. Each technique has limitations that affect how accurately they can characterize small crystalline defects and measure the ice-thickness non-uniformities that may be only a few micrometers in height. The concern is that shadowgraphy may be overly sensitive to the shape and depth of defects in the surface and insufficiently sensitive to the shape of longer-wavelength roughness, while x-ray phase contrast may be too insensitive to defects in the ice surface. Multiple ice layers with different thicknesses (40 to 63 μm), thickness uniformities (peak-valley variations that range from <2- to 12 μm), and crystal defects were analyzed using shadowgraphy and x-ray phase contrast techniques. The results from each method agree when the ice layer is uniformly thick and the crystal lacks defects. That agreement worsens as the number of defects in the surface of the ice layer increases and the roughness that is determined from a shadowgram image of the target’s limb is greater than can be justified by the number of defects that are seen in the target’s front and rear surfaces. The XPC technique is considerably less sensitive to surface defects, in part due to the poorer dynamic range and image resolution compared to shadowgraphy. Localized regions of the ice layer that are thicker or thinner than the average thickness of the layer are reported by shadowgraphy to be smaller in height and footprint (by up to 30%) than by XPC. As a result, the two techniques report different ice layer thicknesses that can vary by up to 10%. Shadowgraphy results from two caustics that trace different paths through the target, and, in theory, image the same ice-vapor surface (but reflect from either the vapor or ice side of the interface) did not consistently characterize the size or shape of ice features to be the same magnitude. Here, the XPC technique provides the best assessment of low-mode (l < 7) roughness in the ice layer. Shadowgraphy results using the strongest caustic is best for detecting the presence of grooves in the ice, though not for quantifying the size of them. If multiple grooves are present it is best to discard and reform the ice layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nondestructive evaluation technique guide

A total of 70 individual nondestructive evaluation (NDE) techniques are described. Information is presented that permits ease of comparison of the merits and limitations of each technique with respect to various NDE problems. An NDE technique classification system is presented. It is based on the system that was adopted by the National Materials Advisory Board (NMAB). The classification system presented follows the NMAB system closely with the exception of additional categories that have been added to cover more advanced techniques presently in use. The rationale of the technique is explained. The format provides for a concise description of each technique, the physical principles involved, objectives of interrogation, example applications, limitations of each technique, a schematic illustration, and key reference material. Cross-index tabulations are also provided so that particular NDE problems can be referred to appropriate techniques.

Vary, A.↗

Near-Net-Shape Processing of Sintered Fibrous Ceramics Achieved

A variety of sintered fibrous ceramic (SFC) materials have been developed over the last 50 years as thermal barrier materials for reentry applications. SFC materials typically exhibit very low thermal conductivities combined with low densities and good thermal stability up to 2500 F. These materials have flown successfully on the space shuttle orbiters since the 1960's. More recently, the McDonnell Douglas Corporation successfully used SFC tiles as a heat shield on the underside of its DC X test vehicle. For both of these applications, tiles are machined from blocks of a specific type of SFC called an alumina-enhanced thermal barrier (AETB). The sizes of these blocks have been limited by the manufacturing process. In addition, as much as 80 to 90 percent of the material can be lost during the machining of tiles with significant amounts of curvature. To address these problems, the NASA Glenn Research Center at Lewis Field entered a cooperative contract with the Boeing Company to develop a vacuum-assisted forming process that can produce large (approximately 4 square feet), severely contoured panels of AETB while saving costs in comparison to the conventional cast-and-machine billet process. For shuttle use, AETB is slurry cast, drained, and fired to form square billets conforming to the shape of the filtration box. The billets are then cut into tiles of the appropriate size for thermally protecting the space shuttle. Processing techniques have limited the maximum size of AETB billets to 21.5 square inches by 6.5-in. thick, but the space shuttles use discrete heat shield tiles no more than 8 to 12 square inches. However, in other applications, large, complex shapes are needed, and the tiling approach is undesirable. For such applications, vacuum-assisted forming can produce large parts with complex shapes while reducing machining waste and eliminating cemented joints between bonded billets. Because it allows contoured shapes to be formed, material utilization is inherently high. Initial estimates show that the amount of material lost during machining can be reduced by 50 percent or more. In addition, a fiber alignment favorable for minimum heat transfer is maintained for all panel shapes since the fibers are aligned parallel to the contoured surface of the forming tool or mold. The vacuum-assisted forming process can complete the entire forming operation in a matter of minutes and can produce multiple parts whose size is limited only by the size of the forming tool. To date, panels as large as 2 square feet have been demonstrated The vacuum-assisted forming process starts with the fabrication of a permeable forming tool, or mold, with the proper part contour. This reusable tool is mounted over an internal rib support structure, as depicted in the diagram, such that a vacuum can be pulled on the bottom portion of the tool. AETB slurry is then poured over and around the tool, liquid is drawn from the slurry, and the part forms over the tool surface. The part is then dried, fired, and finished machined. Future plans include an evaluation of the need for additional coatings and surface-toughness treatments to extend the durability and performance of this material.

Angel, Paul W.↗

Identification of the Electronic and Structural Dynamics of Catalytic Centers in Single-Fe-Atom Material

The lack of model single-atom catalysts (SACs) and atomic-resolution operando spectroscopic techniques greatly limits our comprehension of the nature of catalysis. Herein, based on the designed model single-Fe-atom catalysts with well-controlled microenvironments, we have explored the exact structure of catalytic centers and provided insights into a spin-crossover-involved mechanism for oxygen reduction reaction (ORR) using operando Raman, X-ray absorption spectroscopies, and the developed operando 57 Fe Mössbauer spectroscopy. In combination with theoretical studies, the N-FeN 4 C 10 moiety is evidenced as a more active site for ORR. Moreover, the potential-relevant dynamic cycles of both geometric structure and electronic configuration of reactive single-Fe-atom moieties are evidenced via capturing the peroxido (*O 2 -) and hydroxyl (*OH-) intermediates under in situ ORR conditions. Overall, we anticipate that the integration of operando techniques and SACs in this work shall shed some light on the electronic-level insight into the catalytic centers and underlying reaction mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation, development and application of optimal output feedback theory. Volume 2: Development of an optimal, limited state feedback outer-loop digital flight control system for 3-D terminal area operation

This report contains the development of a digital outer-loop three dimensional radio navigation (3-D RNAV) flight control system for a small commercial jet transport. The outer-loop control system is designed using optimal stochastic limited state feedback techniques. Options investigated using the optimal limited state feedback approach include integrated versus hierarchical control loop designs, 20 samples per second versus 5 samples per second outer-loop operation and alternative Type 1 integration command errors. Command generator tracking techniques used in the digital control design enable the jet transport to automatically track arbitrary curved flight paths generated by waypoints. The performance of the design is demonstrated using detailed nonlinear aircraft simulations in the terminal area, frequency domain multi-input sigma plots, frequency domain single-input Bode plots and closed-loop poles. The response of the system to a severe wind shear during a landing approach is also presented.

Broussard, J. R.↗

Lightweight Lidar Telescopes for Space Applications

NASA is intent on exploiting the unique perspective of space-based remote optical instruments to observe and study large-scale environmental processes. Emphasis on smaller and more affordable missions continues to force the remote sensing instruments to find innovative ways to reduce the size, weight, and cost of the sensor package. This is a challenge because many of the proposed instruments incorporate a high quality meter-class telescope that can be a significant driver of total instrument costs. While various methods for telescope weight reduction have been achieved, many of the current approaches rely on exotic materials and specialized manufacturing techniques that limit availability or substantially increase costs. A competitive lightweight telescope technology that is especially well suited to space-based coherent Doppler wind lidar has been developed through a collaborative effort involving NASA Marshall Space Flight Center (MSFC) through the Global Hydrology and Climate Center (GHCC) and the University of Alabama in Huntsville (UAH) at the Center for Applied Optics (CAO). The new lightweight optics using metal alloy shells and surfaces (LOMASS) fabrication approach is suitable for high quality metal mirrors and meter-class telescopes. Compared to alternative materials and fabrication methods the new approach promises to reduce the areal density of a meter-class telescope to less than 15-kg/sq m; deliver a minimum VIO-RMS surface optical quality; while using commercial materials and equipment to lower procurement costs. The final optical figure and finish is put into the mirrors through conventional diamond turning and polishing techniques. This approach is especially advantageous for a coherent lidar instrument because the reduced telescope weight permits the rotation of the telescope to scan the beam without requiring heavy wedges or additional large mirrors. Ongoing investigations and preliminary results show promise for the LOMASS approach to be successful in demonstrating a novel alternative approach to fabricating lightweight mirrors with performance parameters comparable with the Space Readiness Coherent Lidar Experiment (SPARCLE). Development and process characterization is continuing with the design and fabrication of mirrors for a 25-cm telescope suitable for a lidar instrument.

Peters, Bruce R.↗

Automated Antenna Design with Evolutionary Algorithms

Current methods of designing and optimizing antennas by hand are time and labor intensive, and limit complexity. Evolutionary design techniques can overcome these limitations by searching the design space and automatically finding effective solutions. In recent years, evolutionary algorithms have shown great promise in finding practical solutions in large, poorly understood design spaces. In particular, spacecraft antenna design has proven tractable to evolutionary design techniques. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years as computer speed has increased and electromagnetic simulators have improved. Two requirements-compliant antennas, one for ST5 and another for TDRS-C, have been automatically designed by evolutionary algorithms. The ST5 antenna is slated to fly this year, and a TDRS-C phased array element has been fabricated and tested. Such automated evolutionary design is enabled by medium-to-high quality simulators and fast modern computers to evaluate computer-generated designs. Evolutionary algorithms automate cut-and-try engineering, substituting automated search though millions of potential designs for intelligent search by engineers through a much smaller number of designs. For evolutionary design, the engineer chooses the evolutionary technique, parameters and the basic form of the antenna, e.g., single wire for ST5 and crossed-element Yagi for TDRS-C. Evolutionary algorithms then search for optimal configurations in the space defined by the engineer. NASA's Space Technology 5 (ST5) mission will launch three small spacecraft to test innovative concepts and technologies. Advanced evolutionary algorithms were used to automatically design antennas for ST5. The combination of wide beamwidth for a circularly-polarized wave and wide impedance bandwidth made for a challenging antenna design problem. From past experience in designing wire antennas, we chose to constrain the evolutionary design to a monopole wire antenna. The results of the runs produced requirements-compliant antennas that were subsequently fabricated and tested. The evolved antenna has a number of advantages with regard to power consumption, fabrication time and complexity, and performance. Lower power requirements result from achieving high gain across a wider range of elevation angles, thus allowing a broader range of angles over which maximum data throughput can be achieved. Since the evolved antenna does not require a phasing circuit, less design and fabrication work is required. In terms of overall work, the evolved antenna required approximately three person-months to design and fabricate whereas the conventional antenna required about five. Furthermore, when the mission was modified and new orbital parameters selected, a redesign of the antenna to new requirements was required. The evolutionary system was rapidly modified and a new antenna evolved in a few weeks. The evolved antenna was shown to be compliant to the ST5 mission requirements. It has an unusual organic looking structure, one that expert antenna designers would not likely produce. This antenna has been tested, baselined and is scheduled to fly this year. In addition to the ST5 antenna, our laboratory has evolved an S-band phased array antenna element design that meets the requirements for NASA's TDRS-C communications satellite scheduled for launch early next decade. A combination of fairly broad bandwidth, high efficiency and circular polarization at high gain made for another challenging design problem. We chose to constrain the evolutionary design to a crossed-element Yagi antenna. The specification called for two types of elements, one for receive only and one for transmit/receive. We were able to evolve a single element design that meets both specifications thereby simplifying the antenna and reducing testing and integration costs. The highest performance antenna found using a getic algorithm and stochastic hill-climbing has been fabricated and tested. Laboratory results correspond well with simulation. Aerospace component design is an expensive and important step in space development. Evolutionary design can make a significant contribution wherever sufficiently fast, accurate and capable software simulators are available. We have demonstrated successful real-world design in the spacecraft antenna domain; and there is good reason to believe that these results could be replicated in other design spaces.

Hornby, Gregory S.↗

Quantum computing for finance

Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. Here, we present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modelling, optimization and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle. Quantum computers are expected to surpass classical computers and transform industries. This Review focuses on quantum computing for financial applications and provides a summary for physicists on potential advantages and limitations of quantum techniques, as well as challenges that physicists could help tackle.

97 MATHEMATICS AND COMPUTING↗

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗

Observation of high-pressure polymorphs in bulk silicon formed at relativistic laser intensities

Silicon polymorphs with exotic electronic and optical properties have recently attracted significant attention due to their wide range of useful band gap characteristics. They are typically formed by static high-pressure techniques, which limits the crystal structures that can be made. This constitutes a major obstacle to study these polymorphs and their incorporation into existing technology. Approaches have attempted to address this shortcoming through using dynamic conditions and chemical precursor materials. Here, we report on an approach to create unusual crystal structures deep in the bulk of a silicon crystal by irradiating it with a laser pulse at ultrarelativistic intensity of up to 7.5 × 10 19 W/ c m 2 . Laser-generated electrons with MeV energy swiftly penetrate the target with speed close to the speed of light and deposit their energy into a large volume across the whole thickness of the sample. The relativistic electron current creates, via branching propagation and ionization, high-energy-density conditions for thermodynamically nonequilibrium phase transformation paths into new crystal polymorphs. X-ray microdiffraction and synchrotron x-ray diffraction analyses indicate, along with conventional dc-Si, the presence of exotic silicon structures in the bulk of the laser intact target volume. These structures are identified as body-centered bc8-Si, rhombohedral r8-Si, hexagonal-diamond hd-Si, and the tetragonal Si-VIII, all phases of Si that have previously been made through static techniques. Additionally, simple-tetragonal st12-Si and body-centered tetragonal bt8-Si were observed along with signatures of not yet identified diffraction spots. Both st12-Si and bt8-Si have only been observed in ultrafast laser microexplosion conditions at much lower laser intensity ∼ 10 14 W/ c m 2 and within a micron-thin surface layer. The findings here are supported by direct observation of nanoparticles with high-resolution transmission electron microscopy and corresponding fast Fourier transform analysis of their interatomic distances. The presented analyses of absorbed laser energy, generation of the MeV electron current, and deposition of energy across the whole target thickness provide a solid basis for drawing the conclusion that the observed silicon polymorphs were produced because of laser-generated high-energy electrons fast-penetrating deeply into the bulk of silicon. In contrast to solid-solid transformations, the plasma-solid transitions offer a paradigm for the creation of exotic, high-energy density materials inside the bulk of the sample by using laser pulses at relativistic intensities. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Physics-Based Limiter Redesign and Bit Performance Analysis at The Geysers

As part of a U.S. DOE Geothermal Technologies Office funding opportunity, Geysers Power Company, LLC (GPC), an indirect subsidiary of Calpine Corporation, partnered with Sandia National Labs, EGI at the University of Utah, and Texas A&M University to demonstrate increased drilling performance at The Geysers Geothermal Field. The performance target in the drilling demonstrations is at least a 25% improvement in rates of penetration, with increased footage on bottom for each bit coupled with increased bit life and time drilling. The project leverages advances in oil and gas drilling technologies including PDC bits, along with the physics-based limiter redesign techniques championed in drilling demonstrations conducted at the Utah FORGE geothermal site. The planned drilling demonstrations are being conducted as part of an existing drilling campaign intended to enhance reservoir utilization. The wells are typically drilled to the top of the reservoir with mud and then air-drilled to total depth (TD) through fractured zones at temperatures ≥ 450°F. A major goal of the project is to assess the effectiveness of implementing mechanical specific energy (MSE) and drilling dysfunction diagnosis and remediation in these challenging environments, as well as alternate rock reduction technologies. The first demonstration well has been completed, with 15 PDC bit runs in the 17.5”, 12.25” and 8.5” sections. Initial analysis shows ROP gains in all three sections, especially in the 17.5” and 12.25” sections, compared with conventional roller cone bit runs in the demonstration well and offset wells. However, in the 8.5” hole, wear and damage to the PDC bits resulted in relatively short bit runs. Analysis is underway to take advantage of the positive results and remediate the challenges. This paper provides updates on drilling activities conducted since the Phase 1 demonstration well at GDC-36 which was drilled from November 2023-January 2024. Additional analysis of the bit performance has been conducted. Furthermore, in subsequent wells drilled by GPC, PDC bits have been used extensively, building on the gains realized at GDC-36. GPC has continued to work with bit vendors to identify designs that last longer in the harsh, air-drilled 8.5” portions of the wells. Planning for the Phase 2 demonstration at Prati-44 is ongoing.

15 GEOTHERMAL ENERGY↗

Extending Imaging Volume in Soft X‐Ray Tomography

Soft X‐ray tomography offers rapid imaging of whole, single cells with a few tens of nanometers spatial resolution without fixation or labeling. Herein, this technique is limited to specimens about 10 μm thick, such that applications of soft X‐ray tomography of large human cells or multicellular specimens are not possible. A theoretical and experimental framework for soft X‐ray tomography that enables extension of imaging volumes to 18 μm‐thick specimens is developed. This approach, based on long depth of field and half‐acquisition tomography, is easily applicable to microscopes equipped with a full‐rotation specimen stage. This opens opportunities for imaging large human cells, such as those commonly seen in cancer research, as well as cell‐to‐cell interactions, where two or more cells occupy the same imaging volume.

Ekman, Axel↗