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At least 1,279 records · Page 71

Random-access technique for modular bathymetry data storage in a continental shelf wave refraction program

A study was conducted of an alternate method for storage and use of bathymetry data in the Langley Research Center and Virginia Institute of Marine Science mid-Atlantic continental-shelf wave-refraction computer program. The regional bathymetry array was divided into 105 indexed modules which can be read individually into memory in a nonsequential manner from a peripheral file using special random-access subroutines. In running a sample refraction case, a 75-percent decrease in program field length was achieved by using the random-access storage method in comparison with the conventional method of total regional array storage. This field-length decrease was accompanied by a comparative 5-percent increase in central processing time and a 477-percent increase in the number of operating-system calls. A comparative Langley Research Center computer system cost savings of 68 percent was achieved by using the random-access storage method.

Poole, L. R.↗

Production, quality assurance and quality control of the SiPM Tiles for the DarkSide-20k Time Projection Chamber

The DarkSide-20k dark matter direct detection experiment will employ a 21 m 2 silicon photomultiplier (SiPM) array, instrumenting a dual-phase 50 tonnes liquid argon Time Projection Chamber (TPC). SiPMs are arranged into modular photosensors called Tiles, each integrating 24 SiPMs onto a printed circuit board (PCB) that provides signal amplification, power distribution, and a single-ended output for simplified readout. Tiles are further grouped into Photo-Detector Units (PDUs). This paper details the production of the Tiles and the Quality Assurance and Quality Control (QA-QC) protocol established to ensure their performance and uniformity. The production and QA-QC of the Tiles are carried out at Nuova Officina Assergi (NOA), an ISO-6 clean room facility at LNGS. This process includes wafer-level cryogenic characterisation, precision die attaching, wire bonding, and extensive electrical and optical validation of each Tile. The overall production yield exceeds 83.5%, matching the requirements of the DarkSide-20k production plan. These results validate the robustness of the Tile design and its suitability for operation in a cryogenic environment.

Acerbi, F. [Fondazione Bruno Kessler]↗

Analysis of a crossed Bragg-cell acousto optical spectrometer for SETI

The search for radio signals from extraterrestrial intelligent (SETI) beings requires the use of large instantaneous bandwidth (500 MHz) and high resolution (20 Hz) spectrometers. Digital systems with a high degree of modularity can be used to provide this capability, and this method has been widely discussed. Another technique for meeting the SETI requirement is to use a crossed Bragg-cell spectrometer as described by Psaltis and Casasent (1979). This technique makes use of the Folded Spectrum concept, introduced by Thomas (1966). The Folded Spectrum is a two-dimensional Fourier Transform of a raster scanned one-dimensional signal. It is directly related to the long one-dimensional spectrum of the original signal and is ideally suited for optical signal processing.

Gulkis, S.↗

Ground data systems resource allocation process

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Berner, Carol A.↗

Subscale Injector Testing to Support Ares Engines Development

The J-2X and RS-68B rocket engines are being developed for NASA's Ares I and Ares V launch vehicles. In support of the development of these engines, hot-fire testing on subscale coaxial injectors has been performed at NASA s Marshall Space Flight Center (MSFC) to evaluate performance data relative to injector type, liquid oxygen (LOX) post tip design features, element density and various operating conditions. Shear coaxial injectors with element densities of 1.1, 1.6, and 2.3 elements/in2 and a swirl coaxial injector with element density of 1.6 elements/in2 were evaluated at conditions relevant to the Ares applications. Chamber pressures with oxygen/hydrogen propellants ranged from 815-1630 psig with mixture ratios ranging from 4.7-6.9. Fuel manifold inlet temperatures were varied from 90 to 270 R. Shear coaxial LOX post tip thicknesses ranged from 0.006 in. to 0.0175 in. Modular, water cooled, calorimeter chamber assemblies were used to provide heating rate data and evaluate the effects of characteristic length (L*). Performance was evaluated relative to the resulting characteristic velocity (C*) efficiency. Testing with both the 2.3 and 1.1 elements/in2 shear coaxial injectors demonstrated no improvement in performance of the "thin" tip configuration versus the "thick" tip configuration. The loss in chamber pressure and associated performance loss seen in previous testing at low fuel temperatures could not be reliably repeated, indicating that this loss is not the result of a fluidic process in the injector elements. Further, no performance loss could be demonstrated once a faceplate seal specifically designed for operation with low temperature hydrogen was implemented in the 1.1 elements/sq in shear coaxial injector. Results for the 1.6 elements/sq in swirl injector at cold fuel temperatures showed performance higher than both the 1.6 elements/in2 shear coaxial injector and the 2.3 elements/in2 shear coaxial injector.

Protz, Christopher↗

Use of Grid-Forming Medium-Voltage Power Electronics Hub in a Microgrid Setting: Preprint

This paper presents the application of a new design of a multiport, modular, medium-voltage power electronics hub (M3PE-HUB) in a microgrid setting. The M3PE-HUB system was modeled in a digital real-time simulator (DRTS) and integrated into the Banshee microgrid test system. This paper presents the preliminary DRTS simulation-based results of the M3PE- HUB system connected in a test microgrid system. Verification and validation of the M3PE-HUB architecture and controls in the test microgrid setting are the primary contributions of this work. The results of the operation during the islanding and resynchronization process indicate the feasibility of the proposed architecture in a microgrid setting. This paper also presents results for a system reconfiguration use case where the M3PE- HUB was used to reconfigure the system under a fault condition.

grid forming↗

Controlling the structure and photophysics of fluorophore dimers using multiple cucurbit[8]uril clampings

A modular strategy has been employed to develop a new class of fluorescent molecules, which generates discrete, dimeric stacked fluorophores upon complexation with multiple cucurbit[8]uril macrocycles. The multiple constraints result in a “static” complex (remaining as a single entity for more than 30 ms) and facilitate fluorophore coupling in the ground state, showing a significant bathochromic shift in absorption and emission. This modular design is surprisingly applicable and flexible and has been validated through an investigation of nine different fluorophore cores ranging in size, shape, and geometric variation of their clamping modules. All fluorescent dimers evaluated can be photo-excited to atypical excimer-like states with elongated excited lifetimes (up to 37 ns) and substantially high quantum yields (up to 1). This strategy offers a straightforward preparation of discrete fluorophore dimers, providing promising model systems with explicitly stable dimeric structures and tunable photophysical features, which can be utilized to study various intermolecular processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupling magnons to an opto-electronic parametric oscillator

Hybrid magnonic systems have emerged as versatile modular components for quantum signal transduction and sensing applications owing to their capability of connecting distinct quantum platforms. To date, the majority of the magnonic systems have been explored in a local, near-field scheme, due to the close proximity required for realizing a strong coupling between magnons and other excitations. This constraint greatly limits the applicability of magnons in developing remotely coupled, distributed quantum network systems. On the contrary, opto-electronic architectures hosting self-sustained oscillations have been a unique platform for long-haul signal transmission and processing. Here, we integrated an opto-electronic oscillator with a magnonic oscillator consisting of a microwave waveguide and a Y 3 Fe 5 O 12 (YIG) sphere, and demonstrated strong and coherent coupling between YIG’s magnon modes and the opto-electronic oscillator’s characteristic photon modes—revealing the hallmark anti-crossing gap in the measured spectrum. In particular, the photon mode is produced on-demand via a nonlinear, parametric process as stipulated by an external seed pump. Both the internal cavity phase and the external pump phase can be precisely tuned to stabilize either degenerate or nondegenerate auto-oscillations. Our result lays out a new, hybrid platform for investigating the long-distance coupling and nonlinearity in coherent magnonic phenomena, which may be found useful in constructing the future “distributed hybrid magnonic systems.”

36 MATERIALS SCIENCE↗

Findings on subtask 3.3 – applicability of automated brine chemistry determinations for treatment and recovery processes through facility automation/modularization: engineering design study

Under the Energy & Environmental Research Center’s (EERC’s) ~$\$$22 million Phase II Brine Extraction and Storage Test (BEST) Program, a multimillion-dollar brine treatment technology test bed facility was established in western North Dakota to provide a platform for evaluating developing technologies and approaches for brine treatment and volume reduction. The initial facility, and associated research effort, was funded by the U.S. Department of Energy (DOE), with in-kind contributions provided by several industry participants and the state of North Dakota. Since its opening, the Brine Technology Test Facility (BTTF) has supported performance evaluations of desalination technologies capable of treating high-salinity produced water (PW) and enabled data collection for multiple approaches of PW management and critical material recovery. As part of the decommissioning process for the original project, facility ownership and liability were transferred to Select Water, which is providing the EERC with a continuing site access option for state or federal research and/or commercial technology development. This report documents the findings from a design study conducted by the EERC and the engineering firm that was originally contracted to design and construct the facility (Advanced Engineering and Environmental Services, LLC [AE2S]) that evaluated the current status of BTTF and its systems and developed a retrofit design to increase the facility’s capabilities through automation and modularization of its PW treatment infrastructure. The proposed retrofit will provide DOE and industry with an expanded range of conditioned PW that can be produced at the facility for evaluating fit-for-purpose water treatment technologies, online instrumentation for brine chemistry determination, and systems that recover critical materials like lithium and magnesium. The current facility consists of an 9600-square-foot facility that includes a 40-foot by 65-foot Class 1, Division 2-rated demonstration area and associated control rooms and lab-ready space capable of sourcing oil and gas PW and wastewater from industrial sources or tailoring brine compositions up to 300,000 mg/L total dissolved solids (TDS) and supplying them at rates up to 25 gpm for extended-duration technology demonstrations. The colocation of the facility with Select Water’s water management facilities allows for access and unloading of more than 10,000 bbl/day of trucked water delivered to site and associated access to on-site Class I and Class II brine disposal wells and nearby hazardous waste landfills operated and/or contracted by Select Water to dispose of concentrate and/or effluents associated with the testing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing Heterologous Bacterial Two-Component Systems as Biosensors to Address Challenges in Fermentation Scale-Up

Scaling up bacterial fermentation from bench to industrial scale often results in unpredictable performance losses, possibly in part due to changes in microenvironmental conditions such as pH. To investigate this, we developed a suite of pH-sensitive biosensors from bacterial two-component systems (TCSs) that provide a dynamic, fluorescent readout in response to extracellular pH changes. TCSs consist of a periplasmic sensor histidine kinase (HK) that, in response to an extracellular stimulus, autophosphorylates intracellularly and subsequently transfers the phosphate to a cognate response regulator (RR) that modulates transcription of target genes. We utilized three pH-responsive TCSs (referred to here as CVJ1, CVJ30, and CVJ79) and linked their output to GFP. This was achieved by placing the RR promoter upstream of GFP or by constructing a chimeric RR composed of the native receiver domain and the DNA-binding domain of another well-characterized RR with a defined promoter. All components - HK, RR (native or chimeric), and GFP under its corresponding promoter - were cloned into a broad-host-range plasmid. Sensors were validated in Escherichia coli and Pseudomonas putida, including the muconic acid-producing strain P. putida TL207. All three biosensors successfully reported pH, with fluorescence (normalized to optical density) correlating strongly with media pH. Among the native sensors, CVJ79 showed the most robust performance while CVJ1 also performed best in its native form; CVJ30 exhibited improved functionality as a chimera, suggesting that modular RR design can enhance compatibility in some heterologous hosts. Further, CVJ79 was activated by alkaline conditions, while CVJ30 responded to acidic environments. Notably, CVJ1 was induced by high pH in wild-type E. coli and P. putida, but low pH in TL207. The observed differences in sensor activation between strains - particularly the divergent response of CVJ1 - suggest that host-specific regulatory pathways may influence how cells perceive and adapt to pH stress. Moving forward, these biosensors can be used to guide the rational design of more robust strains, optimize process conditions in real time, and inform strategies to minimize physiological heterogeneity during scale-up. Integrating these tools into high-throughput screening and bioreactors will be a key step toward improving predictability and performance in industrial bioprocesses.

09 BIOMASS FUELS↗

Towards a New Generation of Agricultural System Data, Models and Knowledge Products: Design and Improvement

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Agricultural systems↗

Optical Design and Validation of an Infrared Transmissive Spectrum Splitting Concentrator Photovoltaic Module

A new modular, hybrid solar power system is designed to generate both electrical and thermal energy by utilizing the full solar spectrum. The key element, an infrared-transparent concentrator photovoltaic (CPV) module, acts as a spectrum splitter, dividing solar radiation into two parts. The ultraviolet and visible light (“in-band”) are converted to electricity with high efficiency in CPV cells, while the infrared light (“out-of-band”) is transmitted directly to a thermal receiver, where thermal power may be converted to electricity by a suitable heat engine or used directly for industrial process heat applications whenever needed. Here, we describe the optical design, modeling, fabrication, and performance validation of this novel spectrum splitting CPV module. A transfer matrix style approach, cumulative transmission model, is built to study the reflection, absorption, and transmission in each layer of the CPV module. To optimize the optical performance, different materials for module superstrate/substrate, encapsulant, cell substrate, and cooling fluids are compared in order to enhance the transmission of out-of-band light through the CPV module by minimizing absorption. Six antireflection coatings along with front and backside electrical contact grids are designed to maximize transmittance of in-band light to the cell and out-of-band light to the thermal receiver. Here, the final design, currently being prototyped, predicts out-of-band light transmission to the thermal receiver of 74.1% (for the passively cooled version) and 65.3% (for the actively cooled version). When epitaxial liftoff technology is applied, the transmission will change to 80.8% (passively cooled) and 71.9% (actively cooled). Experimental prototypes show good agreement with modeled optical performance.

14 SOLAR ENERGY↗

Advanced Building Construction (ABC) Research Opportunities Report: Industrializing Construction to Decarbonize Buildings

The DOE Building Technologies Office generally seeks to develop, demonstrate, and accelerate the adoption of cost-effective technologies, techniques, and tools in support of an equitable transition to a decarbonized building stock and energy system by 2050. This ABC Innovations Roadmap specifically focuses on and prioritizes innovations that support the industrialization of whole building retrofits and rapid growth of efficient new construction. The content relates to the integration of technologies and industrialization of processes associated with building construction and renovation. The ABC Innovations Roadmap cross-applies innovations in both the new and existing building sectors with a focus on widescale applicability. Installation flexibility is key to commoditizing solutions that are applicable for a wide variety of buildings (e.g., different building types, vintages, architectural details, and system configurations) and to help simplify decarbonization processes for the workforce.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗

Modular Metal–Organic Polyhedra Superassembly: From Molecular‐Level Design to Targeted Drug Delivery

Abstract Targeted drug delivery remains at the forefront of biomedical research but remains a challenge to date. Herein, the first superassembly of nanosized metal–organic polyhedra (MOP) and their biomimetic coatings of lipid bilayers are described to synergistically combine the advantages of micelles and supramolecular coordination cages for targeted drug delivery. The superassembly technique affords unique hydrophobic features that endow individual MOP to act as nanobuilding blocks and enable their superassembly into larger and well‐defined nanocarriers with homogeneous sizes over a broad range of diameters. Various cargos are controllably loaded into the MOP with high payloads, and the nanocages are then superassembled to form multidrug delivery systems. Additionally, functional nanoparticles are introduced into the superassemblies via a one‐pot process for versatile bioapplications. The MOP superassemblies are surface‐engineered with epidermal growth factor receptors and can be targeted to cancer cells. In vivo studies indicated the assemblies to have a substantial circulation half‐life of 5.6 h and to undergo renal clearance—characteristics needed for nanomedicines.

Zhu, Wei↗

Semantic embedding for quantum algorithms

The study of classical algorithms is supported by an immense understructure, founded in logic, type, and category theory, that allows an algorithmist to reason about the sequential manipulation of data irrespective of a computation’s realizing dynamics. As quantum computing matures, a similar need has developed for an assurance of the correctness of high-level quantum algorithmic reasoning. Parallel to this need, many quantum algorithms have been unified and improved using quantum signal processing (QSP) and quantum singular value transformation (QSVT), which characterize the ability, by alternating circuit ansätze, to transform the singular values of sub-blocks of unitary matrices by polynomial functions. However, while the algebraic manipulation of polynomials is simple (e.g., compositions and products), the QSP/QSVT circuits realizing analogous manipulations of their embedded polynomials are non-obvious. This work constructs and characterizes the runtime and expressivity of QSP/QSVT protocols where circuit manipulation maps naturally to the algebraic manipulation of functional transforms (termed semantic embedding). In this way, QSP/QSVT can be treated and combined modularly, purely in terms of the functional transforms they embed, with key guarantees on the computability and modularity of the realizing circuits. We also identify existing quantum algorithms whose use of semantic embedding is implicit, spanning from distributed search to proofs of soundness in quantum cryptography. The methods used, based in category theory, establish a theory of semantically embeddable quantum algorithms, and provide a new role for QSP/QSVT in reducing sophisticated algorithmic problems to simpler algebraic ones.

Physics↗

Emerging and existing sensing technologies for small modular reactors and advanced reactors - 191

The development of small modular reactors (SMRs) and Generation-IV advanced reactor designs represents a promising future for nuclear energy. These next-generation reactors can support new applications for nuclear energy like hydrogen production, industrial heat generation, and water desalination in addition to electricity generation. Furthermore, SMRs and advanced reactors enable load-following operations, offer improved passive safety features, support lengthened refueling cycles, and provide spent fuel management capabilities. To date, there are no SMRs operating or under construction in the United States, but commercial operation of the first integral Pressurized Water Reactor (iPWR) SMR is expected by the mid-2020's with Generation-IV advanced reactors to follow a decade or two later. To facilitate the development and deployment of SMRs and advanced reactors, key instrumentation and control (I and C) system challenges must be addressed and existing nuclear grade I and C sensors will need to be adapted or new sensors developed. For example, traditional measurement techniques and maintenance strategies used in the current generation of light water reactors (LWRs) will be challenged by the inherent design characteristics of the iPWR. For Generation-IV reactors, conventional I and C sensors will not withstand prolonged exposure to the harsh environmental conditions of advanced reactors (e.g. elevated temperatures, corrosive coolants, increased radiation). This paper discusses the challenges associated with making primary system process measurements in next-generation reactors and includes a summary of work performed to evaluate existing and emerging sensor technologies for these systems. As importantly, the paper presents the initial test results of a prototype temperature sensor developed by Analysis and Measurement Services Corporation (AMS) for use in SMRs and advanced reactors. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗