Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “convergence”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

HPC and Cloud Convergence Beyond Technical Boundaries: Strategies for Economic Sustainability, Standardization, and Data Accessibility

At the IEEE/ACM International Conference for High-Performance Computing, Networking, Storage, and Analysis (SC23), held in Denver, experts discussed the convergence of high-performance computing and cloud computing. Experts explored how this integration could address current scientific computing limitations, enhance computational capabilities, and foster global collaboration while focusing on economic, security, technical, and community challenges and opportunities.

97 MATHEMATICS AND COMPUTING↗

Convergence of Energy and IT Sectors

Today there has never been a more profound codependence and synergetic convergence, such as the one between the energy and IT sectors, and the industries will need to work together more closely to meet today’s growing data center power demands.

AI↗

Converged Computing: A Best of Both Worlds of High-Performance Computing and Cloud

Collaboration between Cloud and High Performance Computing (HPC) communities has accelerated in the last half decade. A common goal to run batch workloads combined with a desire for reproducibility, automation, and optimization has led to successful projects that range from container technologies to workload management and security. This span of current and future work defines a novel “Converged Computing” paradigm that aims to combine the best of both worlds, both from a technological and cultural standpoint. Furthermore, in this Special Issue, we review common themes in the space, showcasing current work and encouraging a continued effort toward innovative ideas that will enable the next generations of scientific discovery.

97 MATHEMATICS AND COMPUTING↗

Three Birds with One Stone: Improving Performance, Convergence, and System Throughput with NEST

Variational quantum algorithms (VQAs) have the potential to demonstrate quantum utility on near-term quantum computers. However, these algorithms often get executed on the highest-fidelity qubits and computers to achieve the best performance, causing low system throughput. Recent efforts have shown that VQAs can be run on low-fidelity qubits initially and high-fidelity qubits later on to still achieve good performance. We take this effort forward and show that carefully varying the qubit fidelity map of the VQA over its execution using our technique, Nest, does not just (1) improve performance (i.e., help achieve close to optimal results), but also (2) lead to faster convergence. We also use Nest to co-locate multiple VQAs concurrently on the same computer, thus (3) increasing the system throughput, and therefore, balancing and optimizing three conflicting metrics simultaneously.

qaoa↗

Convergence QL: NSF/DOE Quantum Science Summer School: QS3 Final Report

Convergence QL: NSF/DOE Quantum Science Summer School (QS3) was a 2-week summer program held in 2017, 2018, 2019, and 2022. The program was aimed at graduate students and postdoctoral researchers working on a wide range of topics related to quantum science and quantum engineering. Expert leaders in this field served as lectures for the school. The school program included lectures, active learning, project activities, poster presentations, and industry panel discussions. The school covered four topics: Fundamentals and Applications of Quantum Computing (2017), Fundamentals and Applications of Quantum Materials (2018), Fundamentals and Applications of Quantum Devices (2019), and Modern Synthesis of Quantum Materials (2022). In terms of intellectual merit, the school brought together students from different areas of research related to quantum science to educate them on a broad range of related topics, providing a unique crucible for the development of educational content and learning opportunities in a cross-disciplinary fashion in the context of quantum science and quantum engineering. In terms of broader impacts, this may serve to create a workforce which would accelerate research in quantum science, quantum engineering, and the development of new quantum technologies beneficial to society. Additionally, this may add to the training of a cadre of scientists and engineers to serve as future leaders in this research field.

42 ENGINEERING↗

Convergent Manufacturing of Large-Scale Components for Nuclear Applications, via Additive Manufacturing and Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy (PM)–hot isostatic pressing (PM-HIP) has long been recognized as a powerful route for producing fully dense, near net shape metallic components. By consolidating powders under high temperature and pressure, HIP provides isotropic properties, uniform microstructures, and scalability to complex geometries that are vital for sectors such as aerospace, energy, and nuclear power. Yet despite these advantages, the technology has remained constrained by costly trial and error canister fabrication, limitations of conventional forging, and incomplete knowledge about how the canister design influences final part properties. Additive manufacturing (AM), by contrast, thrives on design freedom and geometric flexibility but struggles with speed, scalability, and cost when applied to very large structures. The research presented in this report investigated how a convergent manufacturing approach, combining AM with PM-HIP, can merge the strengths of both technologies, leveraging AM’s flexibility for canister design and HIP’s consolidation capability to deliver reliable, large, and complex parts. The work progressed through three case studies that built on one another in scale and complexity. Small cylindrical canisters fabricated by conventional methods, laser powder bed fusion, and directed energy deposition were filled with stainless steel powders and subjected to HIP. The resulting parts demonstrated near-full density and mechanical properties on par with wrought stainless steel, showing for the first time that AM canisters can be a direct substitute for conventional ones without sacrificing quality. The next step involved a medium-scale, noncentrosymmetric T-valve, which is an enclosed, multibranch geometry that tested the limits of AM + PM-HIP integration. The T-valve achieved predictable shrinkage and uniform densification, confirming feasibility for enclosed designs. However, this study also revealed oxide inclusions and interfacial challenges at the AM + HIP boundary, underscoring the critical importance of controlling interface chemistry and employing robust, in situ strategies, such as melt pool monitoring and thermal monitoring, coupled with nondestructive evaluation techniques such as x-ray computed tomography. Finally, the effort culminated in fabricating a large-scale impeller weighing nearly 2000 lb and spanning 5 ft in diameter. Produced via multirobot wire arc AM and hot isostatic pressed to near-full density, the impeller validated industrial-scale feasibility. Predictive models closely matched experimental shrinkage, tensile properties were spatially uniform across the component, and the AM + PM-HIP interface proved mechanically sound despite the presence of oxide-decorated prior particle boundaries. This large-scale demonstration is a major milestone, showing that hybrid AM + PM‑HIP can reliably deliver components at reactor-relevant scales. Collectively, these studies charted a logical pathway: small-scale work built scientific confidence, medium-scale work highlighted opportunities and challenges, and large-scale work proved industrial impact. The overarching conclusion of this report is that AM + PM-HIP should not be seen as a replacement for forging but as a complementary pathway that provides the US with flexibility, resilience, and new options for manufacturing nuclear-grade components. Looking ahead, several directions emerge as critical to sustaining progress. Predictive modeling must become faster, more accessible, and more accurate, with digital twins and machine learning reducing reliance on trial and error. Powders and alloys must be optimized for HIP, with improved cleanliness, reduced oxides, and tailored chemistries that enhance creep, fatigue, and irradiation resistance. Interfaces between AM and HIP regions must be better engineered through coatings, machining strategies, and surface treatments to mitigate oxide formation and ensure reliable bonding to explore opportunities for HIP of targeted compositional parts, as well as multimaterial HIP cladding applications. Monitoring and nondestructive evaluation need to expand, incorporating multimodal sensors, x-ray computed tomography, and real-time data integration through platforms such as Pelican. At the same time, the pathway to industrial adoption requires techno-economic analysis, machinability studies, and qualification frameworks aligned with industry and regulatory standards. Finally, workforce and academic engagement must be strengthened. Programs that train technicians and engineers for US Navy and US Department of Energy manufacturing challenges should be paired with academic partnerships to support fundamental research, with open sharing of non-export-controlled data to accelerate innovation and build the next generation of experts. In conclusion, this report demonstrates that hybrid AM + PM-HIP is scientifically viable and strategically important. By combining the design agility of AM with the consolidation strength of HIP and embedding modeling, monitoring, and workforce development, this approach provided a transformative new capability for US manufacturing. The path forward is clear: hybrid AM + PM-HIP is not just a promising research direction but is also potentially an industrially relevant pathway that can reshape how nuclear-grade components are designed, qualified, and deployed.

36 MATERIALS SCIENCE↗

Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems

Strongly-correlated quantum many-body systems are difficult to study and simulate classically. We recently proposed a variational quantum eigensolver (VQE) based on the multiscale entanglement renormalization ansatz (MERA) with tensors constrained to certain Trotter circuits. Here, we determine the scaling of computation costs for various critical spin chains which substantiates a polynomial quantum advantage in comparison to classical MERA simulations based on exact energy gradients or variational Monte Carlo. Algorithmic phase diagrams suggest an even greater separation for higher-dimensional systems. Hence, the Trotterized MERA VQE is a promising route for the efficient investigation of strongly-correlated quantum many-body systems on quantum computers. Furthermore, we show how the convergence can be substantially improved by building up the MERA layer by layer in the initialization stage and by scanning through the phase diagram during optimization. For the Trotter circuits being composed of single-qubit and two-qubit rotations, it is experimentally advantageous to have small rotation angles. We find that the average angle amplitude can be reduced considerably with negligible effect on the energy accuracy. Benchmark simulations suggest that the structure of the Trotter circuits for the TMERA tensors is not decisive; in particular, brick-wall circuits and parallel random-pair circuits yield very similar energy accuracies.

Miao, Qiang [Duke Quantum Center, Duke University,↗

Convergent evolution of aerobic fermentation through divergent mechanisms acting on the same key glycolytic genes

Expression profiling by high throughput sequencing The model yeast Saccharomyces cerevisiae has evolved aerobic fermentation in part through a whole genome duplication and subsequent retention of glycolytic genes. To identify independent yeast lineages with a high glycolytic rate phenotype we developed an assay measuring extracellular acidification rates (ECAR) to evaluate the glycolytic rates across diverse yeast species. This assay identified a novel group of yeasts in the genus Saturnispora with rapid glycolytic rates. Through comparative approaches, we found that several glycolytic genes encoding hexokinases and enzymes in lower glycolysis had higher expression and modifications in promoter sequences in rapid ECAR species. Intriguingly, many of the upregulated genes are the same genes that are duplicated in S. cerevisiae. When the transcription factor required for their activation was deleted, the mutants had a slow glycolytic rate and more respiratory phenotype. This work shows how the aerobic fermentation phenotype has convergently evolved in Saturnispora through transcriptional rewiring. This divergent mechanism nevertheless impacts the same glycolytic genes, which suggests that there are evolutionary constraints on how aerobic fermentation can arise.

Horianopoulos, Linda C. [Department of Food Scienc↗

Experimental Investigation of Vapor Formation in Liquid CO2 Flow Through a Converging-Diverging Nozzle

Carbon dioxide is an attractive working fluid for many cycles, including for pumped thermal energy storage (PTES). A challenge with some proposed sCO2 PTES cycles is the operation of sCO2 machinery outside the typical bounds of experience, with local phase change from the liquid state being particularly unknown. Presently, there is insufficient data in the literature regarding multiphase CO2 to adequately design a multiphase-tolerant turbine, so generation of foundational data is required. This experimental study investigates the flow characteristics of sub-sonic liquid CO2 undergoing expansion and phase change in a converging-diverging nozzle. The nozzle is instrumented to measure static pressure, unsteady pressure, temperature, and density. The static pressure transducers are located at 27 axial locations to accurately characterize the pressure profile in the nozzle. High-accuracy RTDs are located at the entrance and exit of the nozzle, and three dynamic pressure transducers are strategically located to capture any unsteady phenomena. During testing, values of mass flow and nozzle inlet pressure are swept to vary the pressure drop and fluid properties. The measured total pressure drop in the nozzle is compared to a homogenous model and the Lockhart-Martinelli correlation method, with the latter predicting loss quite closely. The resulting data set is valuable for validating multiphase numerical models in a simple geometry before implementation of these models in turbomachinery design.

25 ENERGY STORAGE↗

Optimizing processing conditions for additively reinforced thermoforming (ART) in convergent manufacturing

This study utilized additively reinforced thermoforming (ART) to enhance the thermomechanical properties of polyethylene terephthalate glycol (PETG) sheet. ART materials were produced by overprinting PETG/carbon fiber filament (PETG/CF) on neat PETG sheets at varying conditions. The mechanical properties of the PETG sheet, PETG/CF, and ART materials were assessed, showing that ART exhibited superior tensile strength and modulus of elasticity. The tensile strength and modulus in the x-direction for ART at 265°C were 57.32 ± 2.9 MPa and 3.41 ± 0.4 GPa, respectively, compared to 49.1 ± 0.5 MPa and 1.92 ± 0.09 GPa for neat PETG. Microstructural analysis revealed strong interfacial adhesion between layers, while thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and heat deflection temperature analysis provided insights into the ART material's thermoforming behavior, aiding design optimization for enhanced stiffness, reduced necking, and improved customization. In conclusion, this information can be used to design for the thermoforming operation.

Additive reinforcement↗

On the convergence of the fixed point method for solving neutron transport alpha eigenvalue problems

It was shown that the Fixed Point Method (also known as the Rayleigh Quotient Method) is several times faster than the Critical Search Method for solving neutron transport alpha eigenvalue problems. It was also shown that the Fixed Point Method is able to determine the alpha eigenvalues of sub-critical systems that are beyond the reach of the Critical Search Method. Despite these significant advances, the Fixed Point Method remains an unproven algorithm. Here, this report provides a proof.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Insights into convergent evolution of cosexuality in liverworts from the Marchantia quadrata genome

Sex chromosomes are expected to coevolve with their respective sex, potentially disfavoring their co-occurrence as cosexuality evolves. This effect is expected to be stronger where sex chromosomes are restricted to one sex, such as in plants expressing sex in their haploid stage. We assess this hypothesis in liverworts with U/V sex chromosomes, ancestral dioicy, and several independent transitions to monoicy (cosexuality). We report the chromosome-level genome assembly of Marchantia quadrata, which recently evolved monoicy, and perform comparative genomic analyses with its dioicous relative M. polymorpha. We find that monoicy evolved via retention of the V chromosome as a small ninth chromosome, complete loss of the U chromosome, and translocation of key U-linked genes to autosomes, among which the major sex-determining gene (Feminizer) acquired environmental/developmental regulation. Our findings parallel recent observations on Ricciocarpos natans, which evolved monoicy independently, suggesting genetic constraints that may make transitions to monoicy predictable in liverworts.

Potente, Giacomo↗

Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke

Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.

Exposure assessment↗

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗

Conduction band convergence and local structure distortion for superior thermoelectric performance of GaSb-doped n-type PbSe thermoelectrics

Achieving high-stability thermoelectric materials with excellent average power factor and figure of merit is crucial for maximizing the output power density and conversion efficiency of thermoelectric devices. In this study, GaSb is added to PbSe as an n-type dopant to form stable solid solutions. Doping with GaSb flattens the conduction band and reduces the energy difference between the Σ and L conduction bands, thereby significantly improving the Seebeck coefficient. Herein, the Ga and Sb atoms co-occupy the vacant Pb sites, unlike in the case of traditional single-element doping, as is verified by density functional theory calculations. The resultant structural distortion is confirmed via transmission electron microscopy. This local structure distortion caused by GaSb doping reduces the lattice thermal conductivity. Consequently, the Pb 0.99875 (GaSb) 0.00125 Se sample exhibits a record-high average power factor of ~22.37 μW cm −1 K −2 and a high average figure of merit of ~0.94 in the temperature range of 300‒873 K. Furthermore, the introduction of interstitial Cu and discordant Zn atoms further reduces the lattice thermal conductivity. The Pb 0.99875 (GaSb) 0.00125 Zn 0.01 Se 1.01 -0.3%Cu sample exhibits a low lattice thermal conductivity of ~0.4 W m −1 K −1 at 873 K and a record-high average figure of merit of ~1.01 in the temperature range of 300‒873 K.

36 MATERIALS SCIENCE↗