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At least 37 records · Page 2

Worst crosstalk analysis in heterogeneous and trench assisted heterogeneous multicore fiber for different core counts and layouts

In order to obtain appreciably low worst crosstalk level in high core count multicore fiber, heterogeneous MCF with different core configurations and layouts have been investigated analytically using coupled mode equation. The variations in worst crosstalk behavior with respect to the bending radius, core configurations, core layouts, and outer cladding thickness have been analyzed. Further, the core count dependent variations in worst crosstalk level, core pitch, and peak bending radius in different core layouts have been presented. It has been observed that the selection of core configuration, core layout, and outer cladding thickness have significant impact on the reduction in worst crosstalk level. For example, in 12-core normal-index heterogeneous MCF with SLS structure, the core Configuration 1 can provide the worst crosstalk level reduced by 7.09 dB and 16.92 dB in comparison to the other two core configurations, i.e., Configuration 2, and Configuration 3, respectively. Further, for the same core count with TA Configuration 1, SLS core layout can achieve the reduced worst crosstalk level in comparison with circular ORS and DRS, hexagonal ORS and DRS respectively by 24.62 dB, 25.86 dB, 28.87 dB and 30.64 dB.

36 MATERIALS SCIENCE↗

Regen: An object layout regenerator on large-scale production HPC systems

This article proposes an object layout regenerator called Regen which regenerates and removes the object layout dynamically to improve the read performance of applications. Regen first detects frequent access patterns from the I/O requests of the applications. Second, Regen reorganizes the objects and regenerates or preallocates new object layouts according to the identified access patterns. Finally, Regen removes or reuses the obsolete or regenerated object layouts as necessary. As a result, Regen accelerates access to objects by providing a flexible object layout. We implement Regen as a framework on top of Proactive Data Container (PDC) and evaluate it on Cori supercomputer, a production-scale HPC system, by using realistic HPC I/O benchmarks. The experimental results show that Regen improves the I/O performance by up to 16.92 × compared with an existing system.

Distributed file system↗

Improving Tumor Treating Fields Treatment Efficacy in Patients With Glioblastoma Using Personalized Array Layouts

Purpose: To investigate tumors of different size, shape, and location and the effect of varying transducer layouts on Tumor Treating Fields (TTFields) distribution in an anisotropic model. Methods and Materials: A realistic human head model was generated from MR images of 1 healthy subject. Four different virtual tumors were placed at separate locations. The transducer arrays were modeled to mimic the TTFields-delivering commercial device. For each tumor location, varying array layouts were tested. The finite element method was used to calculate the electric field distribution, taking into account tissue heterogeneity and anisotropy. Results: In all tumors, the average electric field induced by either of the 2 perpendicular array layouts exceeded the 1-V/cm therapeutic threshold value for TTFields effectiveness. Field strength within a tumor did not correlate with its size and shape but was higher in more superficial tumors. Additionally, it always increased when the array was adapted to the tumor's location. Compared with a default layout, the largest increase in field strength was 184%, and the highest average field strength induced in a tumor was 2.21 V/cm. Conclusions: These results suggest that adapting array layouts to specific tumor locations can significantly increase field strength within the tumor. Our findings support the idea of personalized treatment planning to increase TTFields efficacy for patients with GBM.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Collimated phase measuring deflectometry II: Re-design of the optical layout for high-curvature surfaces

Collimated phase measuring deflectometry (CPMD) is an optical metrology technique developed to improve upon traditional phase measuring deflectometry (PMD). CPMD utilizes telecentric imaging and collimated structured light illumination to eliminate the height-slope ambiguity present in traditional PMD measurements. After the publication of the first CPMD paper, efforts began to optimize the optical layout of the CPMD system. The first proposed change, and the one detailed in this work, was to move the Fourier transform (FT) lens closer to the surface under test (SUT). Moving the FT lens closer to the SUT meant that for a given FT lens diameter, a larger range of surface slopes on the SUT could be measured. This change to the optical layout was not trivial and introduced at least two concerns that had to be addressed: telecentricity in the imaging path and possible ghost reflections from the re-located FT lens. Here, in this work, we examine how these concerns were addressed and present results showing that the revised optical layout is capable of measurement results at least as good as the original CPMD optical layout. We also demonstrate the increased slope measuring range of the revised optical layout.

47 OTHER INSTRUMENTATION↗

Usage Pattern-Driven Dynamic Data Layout Reorganization

As scientific simulations and experiments move toward extremely large scales and generate massive amounts of data, the data access performance of analytic applications becomes crucial. A mismatch often happens between write and read patterns of data accesses, typically resulting in poor read performance. Data layout reorganization has been used to improve the locality of data accesses. However, current data reorganizations are static and focus on generating a single (or set of) optimized layouts that rely on prior knowledge of exact future access patterns. We propose a framework that dynamically recognizes the data usage patterns, replicates the data of interest in multiple reorganized layouts that would benefit common read patterns, and makes runtime decisions on selecting a favorable layout for a given read pattern. This framework supports reading individual elements and chunks of a multi-dimensional array of variables. Our pattern-driven layout selection strategy achieves multi-fold speedups compared to reading from the original dataset.

97 MATHEMATICS AND COMPUTING↗

WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]

WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. It can rapidly estimate the energy production of the plant and turbines for any arbitrarily sized wind plant and layout under any inflow condition. Associated tools include graphing and visualization capabilities as well as a wind plant generator capable of creating randomized realizations of canonical wind plant layouts. The WPGNN architecture and application is extendable to multiple wake models, turbine technologies and features, and supports downstream optimizations of wind plant layouts and control strategies. In addition to the WPGNN, we include the code for the plant layout generator (PLayGen) playgen.py. This generator can produce random realizations of realistic wind plant layouts from one of the four canonical styles: cluster, single string, multiple string, or parallel string. The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.

Harrison-Atlas, Dylan↗

Improving the Spacelab mass memory unit tape layout with a simulation model

A tape drive called the Mass Memory Unit (MMU) stores software used by Spacelab computers. MMU tape motion must be minimized during typical flight operations to avoid a loss of scientific data. A projection of the tape motion is needed for evaluation of candidate tape layouts. A computer simulation of the scheduled and unscheduled MMU tape accesses is developed for this purpose. This simulation permits evaluations of candidate tape layouts by tracking and summarizing tape movements. The factors that affect tape travel are investigated and a heuristic is developed to find a good tape layout. An improved tape layout for Spacelab I is selected after the evaluation of fourteen candidates. The simulation model will provide the ability to determine MMU layouts that substantially decrease the tape travel on future Spacelab flights.

Noneman, S. R.↗

Optimal Control Surface Layout for an Aeroservoelastic Wingbox

This paper demonstrates a technique for locating the optimal control surface layout of an aeroservoelastic Common Research Model wingbox, in the context of maneuver load alleviation and active utter suppression. The combinatorial actuator layout design is solved using ideas borrowed from topology optimization, where the effectiveness of a given control surface is tied to a layout design variable, which varies from zero (the actuator is removed) to one (the actuator is retained). These layout design variables are optimized concurrently with a large number of structural wingbox sizing variables and control surface actuation variables, in order to minimize the sum of structural weight and actuator weight. Results are presented that demonstrate interdependencies between structural sizing patterns and optimal control surface layouts, for both static and dynamic aeroelastic physics.

Stanford, Bret K.↗

Internal Layout of a Lunar Surface Habitat

NASA is currently developing concepts for sustained crewed missions to the lunar surface. Sustained missions will occur on annual basis for durations of 30 days or more. To house and support the crew, NASA is exploring the use of a lunar Surface Habitat. NASA relies on conceptual spacecraft design to assist in planning and mission analysis. A crucial component of this habitation design is the internal layout: the interior location of systems, workstations, crew quarters, etc. The purpose of this paper is to describe the process and resulting layout of a specific Surface Habitat design. This paper describes the SH’s hybrid inflatable structure then details the habitat’s interior layout. The proposed SH’s internal layout is depicted inside a hybrid inflatable structure using a low-fidelity CAD model. Multiple NASA references were consulted to determine the SH’s required functionality, minimal Net Habitable Volume, and minimal functional dimensions. These functions and volumes contribute to the placement and location of systems and spaces inside the habitat. In addition to functional volume, the layout includes systems and logistics placement. The resulting design will aid NASA in mission planning and further systems analysis.

Callie Burke↗

Minimizing total energy cost and tardiness penalty for a scheduling-layout problem in a flexible job shop system: A comparison of four metaheuristic algorithms

Job scheduling and machine layout are interrelated in improving energy consumption (EC) and productivity measures such as tardiness and represent two important decisions that must be made by manufacturers. This interdependency can be explained by transportation time, which connects scheduling and layout. Scheduling and layout, however, have not been thoroughly studied in conjunction using an integrated model in the context of sustainable manufacturing. Hence, we propose an energy-aware optimization model in which scheduling is integrated with layout in a single-level framework. More specifically, a single objective function is defined to minimize the facility energy cost and the job tardiness penalty, which control EC and tardiness respectively in a flexible job shop system. In order to model machine EC more accurately, we also consider three different machine states: a processing state and two idle states. Our case studies show that the integrated model exhibits better performance in controlling manufacturing EC and job tardiness than a non-integrated model in which machine locations are uncontrollable and transportation times between machines are unchangeable. To deal with large-sized problems, we also introduce four new metaheuristics. The performances of these new metaheuristics are compared in terms of objective function values and CPU times using various case studies. The results indicate that a hybrid ant colony optimization and simulated annealing (ACO-SA) algorithm provides better performance than the other algorithms. Specifically, our case studies show that the integrated model using ACO-SA can improve the objective function value by around 5% when compared to the non-integrated model.

42 ENGINEERING↗

Robust wind farm layout optimization

Wake interactions in wind farms cause losses in annual energy production (AEP) on the order of 10%. Wind farm designers optimize the layout of the farm to mitigate wake losses, especially in the dominant site-specific wind directions. As wind turbines and wind farms grow in scale, optimization becomes more complex. Offshore wind farms regularly comprise more than 100 wind turbines and are characterized by complex boundaries due to shipping lanes, neighboring wind farms, and other constraints. Layout optimization methods are broadly split between gradient-based and gradient-free approaches. Gradient-based approaches can converge quickly and perform well for smaller, academic problems but are often sensitive to initial conditions and tuning parameters and require expert knowledge to use. On the other hand, gradient-free approaches can be more robust to problem complexities. We present a robust layout optimization approach based on a random search algorithm. The algorithm is intended for those who are not optimization experts and has few tuning parameters that need specification to achieve satisfactory results. Unlike off-the-shelf methods, which use generally available, non-domain-specific optimization routines that accept as inputs an optimization function and constraint definitions, this approach takes advantage of the relative computational costs of the different evaluations by evaluating cheaper computations first (boundary and minimum distance constraints) and running expensive AEP evaluations only if all other checks pass. Moreover, an outer genetic algorithm allows multiple solutions to evolve in parallel, enabling rapid solution development on high-performance computers. We discuss the relative ease of selecting necessary tuning parameters and demonstrate the efficacy of the genetic random search on a complex layout problem consisting of placing 70 turbines in a nonconvex and unconnected boundary region.

17 WIND ENERGY↗

Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients

Wind farm layout optimization (WFLO) studies often aim to maximize the annual energy production (AEP) of a wind farm by choosing an arrangement of turbines that minimizes wake interactions. One way to reduce the cost of WFLO studies is by using more computationally efficient AEP models. The cost of standard AEP modeling approaches, based on the numerical integration of low-fidelity engineering wake models, scales poorly with the number of simulated discrete wind conditions. A second way to reduce cost when using a gradient-based algorithm is to supply exact gradient information instead of finite-difference estimates. However, analytical functions for the derivatives of AEP with respect to turbine positions are not always available in the conventional modeling approach. FLOWERS is a computationally inexpensive, analytical model for wind farm AEP that is specifically developed for WFLO applications. In this paper, we analyze the performance of the FLOWERS AEP model with analytic gradients in a layout optimization study compared with a reference optimization framework across three wind farm case studies. We find that the FLOWERS-based approach reduces computation time by a factor of 50–4000 and improves optimal AEP by about 0.3% with less than half of the variability in AEP across instances with randomized initial conditions. We also find the optimal layouts to be insensitive to model parameter tuning, making FLOWERS-based layout optimization a streamlined, user-friendly approach.

17 WIND ENERGY↗

Integrated floating wind farm layout design and mooring system optimization to increase annual energy production

As we cluster wind turbines in wind farms to gain energy from sites with high wind speeds, wake losses occur within the wind farm. Wake loss is a term used to describe the lower energy production of a downwind turbine that is totally or partially in the wake of an upwind turbine. To decrease wake losses inside the wind farm, the wind farm’s layout is optimized. However, a variety of factors constrain the wind farm layout optimization, such as the size of the lease area relative to the number of turbines to be placed, or the shape of the lease area. Therefore, many wind farms end up with a regular grid layout, such as the Horns Rev 1 wind farm in the North Sea. The ability of a floating offshore wind turbine (FOWT) to change its position based on the wind direction and its mooring system design presents an opportunity to further decrease wake losses in floating wind farms. In this work, we integrate the design of the FOWT mooring systems with the floating wind farm layout design with the goal of increasing the farm’s annual energy production. We use the Horns Rev 1 wind farm as a case study to demonstrate our method. The results show that allowing the FOWT to relocate can decrease wake losses up to 18%. Moreover, the newly developed mooring systems are less stiff and therefore allow larger motion of the FOWT; hence, the material cost of the mooring system decreases by an estimated 17%.

17 WIND ENERGY↗

IC layout adjustment method and tool for improving dielectric reliability at interconnects

Method for adjusting a layout used in making an integrated circuit includes one or more interconnects in the layout that are susceptible to dielectric breakdown are selected. One or more selected interconnects are adjusted to increase via to wire spacing with respect to at least one via and one wire of the one or more selected interconnects. Preferably, the selecting analyzes signal patterns of interconnects, and estimates the stress ratio based on state probability of routed signal nets in the layout. An annotated layout is provided that describes distances by which one or more via or wire segment edges are to be shifted. Adjustments can include thinning and shifting of wire segments, and rotation of vias.

42 ENGINEERING↗

Sensitivity analysis of design parameters in RowWise borehole layout for ground heat exchangers

Ground source heat pump systems offer a promising pathway toward energy-efficient building heating and cooling. The performance and cost-effectiveness of these systems heavily depend on the design of the ground heat exchanger (GHE), particularly the spatial placement of boreholes used in large commercial buildings. Among various borefield layout strategies, the RowWise approach generates and optimizes borehole configurations within irregular polygonal land boundaries, providing land-use efficiency and installation flexibility. While multiple geometric design parameters constrain the RowWise layout, their influence on the system thermal performance and total drilling requirements remains unclear. Thus, this study presents a sensitivity analysis of key design parameters influencing the RowWise layout of vertical borehole GHEs, including the perimeter spacing ratio, borehole spacing, borehole field rotation angle, and borehole length. GHEDesigner and Ray Tune are employed to generate and assess different RowWise configurations. A series of parametric simulations was conducted to quantify the impact of each parameter on geometric distribution, economic cost, and computational speed. The results provide critical insights into the sensitivity and relative importance of different design parameters of RowWise method, offering practical guidance for designers aiming to optimize GHE layouts by balancing thermal efficiency, land constraints, and economic feasibility.

Xu, Dikai [Purdue University]↗

Wind Farm Layout Optimization with Loads Considerations

The objective of this paper is to improve the annual energy production of a wind farm by optimizing the layout of a wind farm, while considering fatigue loads on turbines. In this paper, the loads are estimated using the edgewise bending moment computed using CCBlade, a steady-state blade element momentum code. The edgewise bending moment is then used to calculate fatigue damage using Miner's rule. The fatigue damage is used to constrain the layout optimization problem. We show that our method can predict blade root damage with similar trends to damage calculated with other methods, such as a complex, computationally expensive large-eddy simulation and unsteady aeroelastic code. We also optimize wind farm layouts and show that, for a simple problem with two wind directions and ten turbines, the fatigue damage can be constrained without sacrificing wind farm power production.

17 WIND ENERGY↗

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and write performance. We demonstrate the benefits of using these two approaches for the ECP particle-in-cell simulation WarpX, which serves as a motif for a large class of important Exascale applications. Here, we show that by understanding application I/O patterns and carefully designing data layouts we can increase read performance by more than 80 percent.

97 MATHEMATICS AND COMPUTING↗

Best Practices for Wake Model and Optimization Algorithm Selection in Wind Farm Layout Optimization

This paper presents the results of two case studies regarding the wind farm layout optimization problem. We asked a general audience to take part in the studies that we designed, and nine individuals participated. Case study 1 considered variations in optimization strategies for a given simple Gaussian wake model. Participants were provided with a wake model that outputs annual energy production (AEP) for an input set of wind turbine locations. Participants used an optimization method of their choosing to find an optimal wind farm layout. Case study 2 looked at trade-offs in performance resulting from variation in both physics model and optimization strategy. For case study 2, participants calculated AEP using a wake model of their choice while also implementing their chosen optimization method. Participants then used their wake model to calculate the AEP all other participant submitted turbine configurations produce for cross-comparison results. for optimized turbine locations were then cross-compared by recalculating the AEP using every other participant's wake model. Results for case study 1 show that the best optimal wind farm layouts in this study were achieved by participants who used gradient-based optimization methods. A front-runner emerged with the Sparse Nonlinear OPTimizer plus Wake Expansion Continuation (SNOPTplusWEC) optimization method, which consistently discovered a higher AEP for each scenario. Results for case study 2 show that for small wind farms with few turbines, turbine placement on the wind farm boundary is superior. Conclusions for case study 2 were drawn from participant cross-comparison of results.

17 WIND ENERGY↗