Arrays Of Different Sizes Research Articles

Physics-constrained Gaussian process model for prediction of hydrodynamic interactions between wave energy converters in an array

To improve the efficiency of wave farms and achieve maximum power generation, the layout of wave energy converters (WECs) in an array needs to be carefully designed so that the hydrodynamic interactions can be positively exploited. For this, the hydrodynamic characteristics of the WEC array in different layouts need to be calculated. However, such calculations using numerical models usually entail significant computational cost, especially for large arrays of WECs. To address the computational challenge, a physics-constrained Gaussian process (GP) model is proposed to replace the original expensive numerical model and predict the hydrodynamic characteristics of the WECs for any array layout. By exploring the relationship between the WEC array (i.e., the input) and different hydrodynamic characteristics (i.e., the output), we summarize a set of physical constraints/features, including invariance, symmetry, and additivity. This prior knowledge about the input-output relationship is then directly embedded in the constructed GP model through the design of physics-constrained kernels. In particular, a double-sum invariant kernel is first developed to incorporate the invariance and symmetry features, and then an additive kernel is developed to incorporate the additive feature of the problem. The invariant kernel and the additive kernel are then integrated to construct the physics-constrained GP model. Compared to the standard GP model, the proposed physics-constrained GP models require less training data to achieve the desired accuracy in predicting the hydrodynamic characteristics and are also less vulnerable to the curse of dimensionality (i.e., good scalability for large arrays) due to the use of an additive kernel. The efficiency, accuracy, and scalability of the proposed approach are demonstrated through an application to predict the hydrodynamic characteristics for WEC arrays of different sizes and layouts.

Effect of reduced genomic representation on using runs of homozygosity for inbreeding characterization.

Genomic measures of inbreeding based on identical-by-descent (IBD) segments are increasingly used to measure inbreeding and mostly estimated on SNP arrays and whole-genome sequencing (WGS) data. However, some softwares recurrently used for their estimation assume that genomic positions which have not been genotyped are nonvariant. This might be true for WGS data, but not for reduced genomic representations and can lead to spurious IBD segments estimation. In this project, we simulated the outputs of WGS, two SNP arrays of different sizes and RAD-sequencing for three populations with different sizes and histories. We compare the results of IBD segments estimation with two softwares: runs of homozygosity (ROHs) estimated with PLINK and homozygous-by-descent (HBD) segments estimated with RZooRoH. We demonstrate that to obtain meaningful estimates of inbreeding, RZooRoH requires a SNPs density 11 times smaller compared to PLINK: ranks of inbreeding coefficients were conserved among individuals above 22 SNPs/Mb for PLINK and 2 SNPs/Mb for RZooRoH. We also show that in populations with simple demographic histories, distribution of ROHs and HBD segments are correctly estimated with both SNP arrays and WGS. PLINK correctly estimated distribution of ROHs with SNP densities above 22 SNPs/Mb, while RZooRoH correctly estimated distribution of HBD segments with SNPs densities above 11 SNPs/Mb. However, in a population with a more complex demographic history, RZooRoH resulted in better distribution of IBD segments estimation compared to PLINK even with WGS data. Consequently, we advise researchers to use either methods relying on excess homozygosity averaged across SNPs or model-based HBD segments calling methods for inbreeding estimations.

Techno-economic analysis of a hybrid photovoltaic-thermal solar-assisted heat pump system for domestic hot water and power generation

This work investigates the techno-economic performance of a hybrid photovoltaic-thermal (PVT) solar-assisted heat-pump system for covering the electrical and hot-water demands of a three-bedroom terraced house in Belfast, United Kingdom with four occupants. This system combines a water-to-water heat pump with PVT panels to deliver both electricity and hot water for domestic consumption. The PVT array provides a source of low-temperature heat for the water-to-water heat pump, while cooling the PVT array and thus preventing the electrical efficiency degradation that occurs at higher operating temperatures. Analyses have been performed for PVT arrays of different size, including 12-panel, 20-panel and 24-panel systems. Results show that, thanks to its lower initial investment cost, the most economically viable system configuration for the household considered in this work is based on a 12-panel PVT array covering a total area of 16.3 m2. This system has the potential to produce 2.4 MWh of (gross) electricity and 2.0 MWh of hot water per year, which is equivalent to just over 30% of the electrical and 80% of the hot-water demands of the household under consideration, with the PVT array acting to reduce the electricity consumption of the heat pump in the heating system by a little over 60%. The system has lower recurring yearly costs relative to current household energy systems that use electricity from the grid and natural gas, despite having higher investment costs. It is also found that the system can reduce the investigated household's annual CO2 emissions by 910 kg per year (about 18 tonnes over a lifetime of 20 years) and that, with an electricity generation incentive rate of 5 p/kWh and a heat generation incentive rate of 21 p/kWh, the aforementioned system has a discounted payback period of 14 years.

Optical characterization and emission enhancement property of Ag nanomesh structure fabricated by nanosphere lithography

A metal nanomesh structure with regularly arranged nanosized holes has a light transmission property at a certain wavelength region and good conductivity; therefore, it can be applied to the wavelength-selective electrode of optical devices such as organic light-emitting diodes (OLEDs) and solar cells. In this study, Ag nanomesh structures with hole arrays of different sizes and periods were fabricated, and their electrical and optical properties were evaluated. Alq3, a green light-emitting material for OLEDs, was deposited on the fabricated Ag nanomesh, and its transmission, scattering, and photoluminescence (PL) spectra were investigated. The PL intensity of Alq3 was approximately four times higher than that without the Ag nanomesh. Time-resolved PL measurements showed the presence of a short-lived component in all samples with Ag nanomesh, indicating plasmonic emission enhancement. These results indicate that Ag nanomeshes can be applied as plasmonic electrodes in optical devices.

Self-rectifying resistive memory in passive crossbar arrays

Conventional computing architectures are poor suited to the unique workload demands of deep learning, which has led to a surge in interest in memory-centric computing. Herein, a trilayer (Hf0.8Si0.2O2/Al2O3/Hf0.5Si0.5O2)-based self-rectifying resistive memory cell (SRMC) that exhibits (i) large selectivity (ca. 104), (ii) two-bit operation, (iii) low read power (4 and 0.8 nW for low and high resistance states, respectively), (iv) read latency (<10 μs), (v) excellent non-volatility (data retention >104 s at 85 °C), and (vi) complementary metal-oxide-semiconductor compatibility (maximum supply voltage ≤5 V) is introduced, which outperforms previously reported SRMCs. These characteristics render the SRMC highly suitable for the main memory for memory-centric computing which can improve deep learning acceleration. Furthermore, the low programming power (ca. 18 nW), latency (100 μs), and endurance (>106) highlight the energy-efficiency and highly reliable random-access memory of our SRMC. The feasible operation of individual SRMCs in passive crossbar arrays of different sizes (30 × 30, 160 × 160, and 320 × 320) is attributed to the large asymmetry and nonlinearity in the current-voltage behavior of the proposed SRMC, verifying its potential for application in large-scale and high-density non-volatile memory for memory-centric computing.

Experimental investigation of the effect of cylindrical array structure on heat transfer performance during nucleate boiling

Using deionized water as the working fluid, a visualized pool boiling study was carried out on the surface of cylindrical pillar arrays of different sizes and the ordinary smooth surface under atmospheric pressure, and the boiling heat transfer curve and the change of heat transfer coefficient were studied. A high-speed camera is used to quantitatively measure the bubble dynamics, including bubble departure diameter and nucleation sites density. The results show that the onset of nucleate boiling temperature of all cylindrical pillar arrays has been significantly reduced, while the heat transfer coefficient is increased by 23.4%-163.4% compared to that of the smooth surface. The decrease of the pillar spacing helps to improve the performance of boiling heat transfer. The smaller gap optimizes the capillary flow of the liquid to a certain extent, thus facilitating the departure of bubbles, thereby inducing the working fluid to quickly replenish the dry area. The reduction of the diameter of the pillars is beneficial to improve the boiling heat transfer performance. More nucleation sites on the wall promote the bubbles to merge more quickly and reach the bubble departure diameter more easily, thus enhancing the evaporation of the micro-liquid layer and promoting the heat transfer. The correlation expressions as well as the upper and lower limits are obtained by fitting the change of heat transfer coefficient curve. Compared with the data in the literature, the S6 surface with the best performance shows obvious heat transfer advantages.

Floating photovoltaics could mitigate climate change impacts on water body temperature and stratification

Floating solar photovoltaics, or floatovoltaics (FPV), are a relatively new form of renewable energy, currently experiencing rapid growth in deployment. FPV decarbonises the energy supply while reducing land-use pressures, offers higher electricity generating efficiencies compared to ground-based systems and reduces water body evaporation. However, the effects on lake temperature and stratification of FPV both sheltering the water’s surface from the wind and limiting the solar radiation reaching the water column are unresolved, despite temperature and stratification being key drivers of the ecosystem response to FPV deployment. These unresolved impacts present a barrier to further deployment, with water body managers concerned of any deleterious effects. To overcome this knowledge gap, here the effects of FPV-induced changes in wind speed and solar radiation on lake thermal structure were modelled utilising the one-dimensional process-based MyLake model. To resolve the effect of FPV arrays of different sizes and designs, observed wind speed and solar radiation were scaled using a factorial approach from 0% to 100% in 1% intervals. The simulations returned a highly non-linear response, dependent on system design and coverage. The responses could be either positive or negative, and were often highly variable, although, most commonly, water temperatures reduce, stratification shortens and mixed depths shallow. Modifications to the thermal dynamics of the water body may subsequently drastically alter biogeochemical processes, with fundamental implications for ecosystem service provision and water treatment costs. The extreme nature of response for particular wind speed and solar radiation combinations results in impacts that could be comparable to, or more significant than, climate change. As such, depending on how they are used, FPV have the potential to mitigate some of the impacts of climate change on water bodies and could be a useful tool for water body managers in dealing with changes to water quality, or, conversely, they could induce deleterious impacts on standing water ecosystems. These simulations provide a starting point to inform the design of future systems that maximise ecosystem service and environmental co-benefits from this growing water body change of use.

Prospects for Wideband VLBI Correlation in the Cloud

This paper proposes a cloud architecture for the correlation of wide bandwidth Very Long Baseline Interferometry (VLBI) data. Cloud correlation facilitates processing of entire experiments in parallel using flexibly allocated and practically unlimited compute resources. This approach offers a potential improvement over dedicated correlation clusters, which are constrained by a fixed number of installed processor nodes and playback units. Additionally, cloud storage offers an alternative to maintaining a fleet of hard disk drives that might be utilized intermittently. Here, we describe benchmarks of VLBI correlation using the DiFX-2.5.2 software on the Google Cloud Platform to assess cloud-based correlation performance. In our analysis, the number of virtual central processing units per virtual machine was varied to determine the optimum configuration of cloud resources. The number of stations was varied to determine the scaling of correlation time with VLBI arrays of different sizes. Data transfer rates from Google cloud storage to the virtual machines performing the correlation were also measured. Based on the results, we present an example cloud correlation configuration. Current cloud service and equipment pricing data is used to compile cost estimates allowing an approximate economic comparison between cloud and cluster processing. We note that the economic comparisons are based on cost figures which are a moving target, and are highly dependent on factors such as the utilization of cluster and media, which are a challenge to estimate. Our model suggests that shifting to the cloud is an alternative path for high data rate, low duty cycle wideband VLBI correlation that should continue to be explored. In the production phase of VLBI correlation, the cloud has the potential to significantly reduce data processing times and allow the processing of more science experiments in a given year for the petabyte-scale data sets increasingly common in both astronomy and geodesy VLBI applications.

29.1: Invited Paper: A Study on the Micro‐Lens Arrays Combination based Optical Film for Optical Field Optimized Projection Display

Owning to the fast development of projection technologies, the large‐scale projection has great potential application for various viewing circumstances in open spaces. This paper reports a novel type of optical imaging film (G2‐HK‐FP) which comprised of a combination of micro‐lens arrays of different sizes and an ambient light rejection design. This film exhibited comparable displaying performance with silver screen film in the dark environment, and superior performance in the ambient light condition in the aspects of relative contrast, color gamut and ambient light rejection efficiency.

Characterization of a Cs2LiYCl6: Ce3+ scintillator coupled with two silicon photomultiplier arrays of different sizes

Neutrons produced by cosmic rays comprise the main factor in radiation hazards for astronauts and spacecraft during space exploration. A silicon-photomultiplier- (SiPM-) array-coupled Cs2LiYCl6: Ce3+ (CLYC) detector was proposed to measure neutrons onboard spacecraft. Since both light-collection efficiency and thermal noise rate are proportional to a SiPM’s size, it is necessary to compare CLYC’s characterization when coupled with SiPM arrays of different sizes. In this paper, a 4×4 array and an 8×8 array, both of which are composed of 3×3-mm2 SiPM elements, were coupled to a Φ38 mm×38 mm cylindrical CLYC detector. The energy resolution, pulse-shape-discrimination (PSD) performance, and temperature dependence were tested with two gamma-ray sources and a neutron source. Results indicate that both energy resolution and PSD performance mainly benefit from the higher light-collection efficiency of the large array. The peak centroids of 137Cs varied by ∼20% in the testing temperature region from -35 °C to +55 °C.

Power and mismatch losses mitigation by a fixed electrical reconfiguration technique for partially shaded photovoltaic arrays

Abstract Partial shading is the most commonly occurring scenario among the modules of the photovoltaic arrays invoking power and mismatch losses. To attenuate these losses, various interconnection topologies for partial shading mitigation have been proposed in the literatures. This paper proposes a fixed electrical reconfiguration technique for the modules that facilitates distribution of the effect of shading in the entire array thereby reducing the losses caused by partial shading. The technique proceeds with renumbering of the modules according to the proposed algorithm followed by electrical rewiring. The entire study has been accomplished by using MATLAB/Simulink environment and field experiment for the arrays of different sizes. The validity of the proposed technique has been critically evaluated using various artificially created shadings and compared with the hitherto known conventional and hybrid topologies. The response of the array having various topologies for every shade condition has been analysed using the characteristics curves and various performance parameters. From the study, it has been found that the proposed technique excels in performance in terms of reducing the number of peaks in the characteristics curves and maximizing power generation during all shade scenarios as compared to other topologies.

A Test Prioritization Algorithm That Cares for "Don't Care" Values and Higher Order Combinatorial Coverage

The efficiency of prioritization algorithms depends on how early the faults are detected. In this paper, we present a novel prioritization algorithm for combinatorial testing. Our approach takes ACTS tool generated test cases with "don't care" values as the starting point and refines them for increased effectiveness without increasing the number of test cases. Our algorithm maximizes the number of higher order combinations tested, by filling the "don't care" values in the test suite effectively. It also orders the test cases using a cost function that includes higher order coverage, thereby achieving early fault detection. The effectiveness of our algorithms is demonstrated by performing a comparative evaluation using the metric t way Rate of Fault Detection, on 2 real life case studies and numerous synthetic covering arrays of different sizes. The results show that our algorithms perform better in terms of covering higher order pairs and also faster.

Analysis and Design of a Thermoelectric Energy Harvesting System With Reconfigurable Array of Thermoelectric Generators for IoT Applications

In this paper, a novel thermoelectric energy harvesting system with a reconfigurable array of thermoelectric generators (TEGs), which requires neither an inductor nor a flying capacitor, is proposed. The proposed architecture can accomplish maximum power point tracking (MPPT) and voltage conversion simultaneously via the reconfiguration of the TEG array, and demonstrate significantly improved power conversion efficiency over the conventional switching converter and switched-capacitor architectures. Two systematical scaling approaches—powers-of-two scaling and maximum-factor scaling—are presented and analyzed to serve as the design guideline, catering for reconfigurable TEG arrays of different sizes. In order to optimize the chip area required, a custom-designed, multi-level hierarchy and systematically scalable switch array that requires a reasonable number of switches is also developed to enable the reconfiguration of the TEG array. The 16-node and 12-node versions of the proposed system have been implemented in a standard 0.35- $\mu \text{m}$ CMOS process. Measurement results verify the analysis, and confirm that the proposed system can maintain a higher than 88.8% efficiency over a wide range of temperature gradients.

RCS Reduction With a Dual Polarized Self-Complementary Connected Array Antenna

In this paper, a wideband dual polarized self-complementary connected array antenna with low radar cross section (RCS) under normal and oblique incidence is presented. First, an analytical model of the multilayer structure is proposed in order to obtain a fast and reliable predimensioning tool providing an optimized design of the infinite array. The accuracy of this model is demonstrated thanks to comparative simulations with a full wave analysis software. RCS reduction compared to a perfectly conducting flat plate of at least 10 dB has been obtained over an ultrawide bandwidth of nearly 7:1 at normal incidence and 5:1 (3.8 to 19 GHz) at 60° in both polarizations. These performances are confirmed by finite element tearing and interconnecting computations of finite arrays of different sizes. Finally, the realization of a 28 × 28 cell prototype and measurement results are detailed.

Time-Averaged Realistic Maximum Power Levels for the Assessment of Radio Frequency Exposure for 5G Radio Base Stations Using Massive MIMO

In this paper, a model for time-averaged realistic maximum power levels for the assessment of radio frequency (RF) electromagnetic field (EMF) exposure for the fifth generation (5G) radio base stations (RBS) employing massive MIMO is presented. The model is based on a statistical approach and developed to provide a realistic conservative RF exposure assessment for a significant proportion of all possible downlink exposure scenarios (95th percentile) in-line with requirements in a recently developed International Electrotechnical Commission standard for RF EMF exposure assessments of RBS. Factors, such as RBS utilization, time-division duplex, scheduling time, and spatial distribution of users within a cell are considered. The model is presented in terms of a closed-form equation. For an example scenario corresponding to an expected 5G RBS product, the largest realistic maximum power level was found to be less than 15% of the corresponding theoretical maximum. For far-field exposure scenarios, this corresponds to a reduction in RF EMF limit compliance distance with a factor of about 2.6. Results are given for antenna arrays of different sizes and for scenarios with beamforming in both azimuth and elevation.

A software tool for testing maximum power point tracking algorithms using real working conditions

This paper presents a software application developed to study and compare maximum power point tracking (MPPT) algorithms for photovoltaic (PV) systems. This user-friendly simulation tool is designed to image a PV system. The first edition of this tool contains a database of real time working conditions (solar irradiance and ambient temperature) based on four PV module's models (B-model, one diode based model, two diodes based model and Akbaba model), a boost DC–DC inverter with MPPT, several MPPT algorithms and a resistive load. The advantage of this work is that it permits to easily redo simulations to study the efficiency of the whole system by changing only one or more of the studied parameters. A great number of combinations are then possible: PV arrays of different sizes, different MPPT algorithms, and different working conditions allowing the analysis of the static and dynamic behavior of the MPPT algorithms. The available database allows the choice of different profiles for solar irradiance: sunny days with smooth variations and cloud covered days with sudden variations to simulate static and dynamic working conditions respectively. In addition to the comparison of the MPPT algorithms efficiency, this tool is of major interest for the analysis of the behavior of each MPPT algorithm.

Performance of Planar Arrays for Microwave Power Transmission With Position Errors

An analytical method based on Statistical Analysis (SA) is proposed to predict the influence of position errors of planar array elements on microwave power transmission (MPT) efficiency. The average power pattern of arrays with arbitrary shape is formulated according to the rules of probability method. Then a closed-form expression describing the relationship between position errors and the average beam collection efficiency (BCE) is derived. A set of representative numerical experiments dealing with planar arrays of different sizes and shapes is reported and discussed to point out the effect of the position errors on MPT.

Stress distribution of 12 μm thick crack free continuous GaN on patterned Si(110) substrate

AbstractThe stress distribution on crack free thick continuous GaN film (12 µm) grown by Metal organic chemical vapour deposition (MOCVD) on the arrays of different sizes of the patterned silicon substrate is investigated by micro‐Raman (µRaman) spectroscopy. On the largest crack free mesa (400 μm) both µ‐photoluminescence (µPL) at low temperature and µRaman measurements are performed. The µRaman shift of the GaN E2 mode shows the U‐shape in‐plane stress distribution across the mesa. The center of the mesa is under tensile stress and it relaxes near the corner and edges. A similar trend is observed also from the µPL spectra. The size of the mesa, the trench height and the trench width of the patterned silicon are varied to study the stress of the thick epitaxial crack free GaN layer. The size and trench height of the mesa have a large influence on the GaN film stress but the trench width does not show any significant effect. The maximum stress is saturated for the large sizes of mesas. (© 2012 WILEY‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)

Design of experiments and integer linear programming-assisted conjugate-gradient optimisation of high-κ/metal-gate nano-complementary metal-oxide semiconductor static random access memory

Low-power consumption and stability in static random access memories (SRAMs) is essential for embedded applications. This study presents a novel design flow for power minimisation of nano-complementary metal-oxide semiconductor SRAMs, while maintaining stability. A 32 nm high-κ/metal-gate SRAM has been used as an example circuit. The baseline circuit is subjected to power minimisation using a dual-threshold voltage assignment based on novel combined design of experiments and integer linear programming (DOE-ILP) approach. However, this leads to a 15% reduction in the static noise margin (SNM) of the cell. The conjugate gradient optimisation overcomes this SNM degradation, while reducing the power consumption. The final SRAM design shows 86% reduction in power consumption (including leakage) and 8% increase in the SNM compared with the baseline design. The variability analysis of the optimised cell is performed by considering the effect of 12 parameters. SRAM arrays of different sizes are constructed to demonstrate the feasibility of the proposed SRAM cell. To the best of the authors’ knowledge, this is the first study which makes use of DOE-ILP and conjugate gradient method for simultaneous stability and power optimisation in high-κ/metal-gate SRAM circuits.

Assessing the Location of Surface Plasmons Over Nanotriangle and Nanohole Arrays of Different Size and Periodicity

The increasing popularity of surface plasmon resonance (SPR) and surface enhanced Raman scattering (SERS) sensor design based on nanotriangle or nanohole arrays, and the possibility to manufacture substrates at the transition between these plasmonic substrates, makes them ideal candidates for the establishment of structure-property relationships. This work features near diffraction-limited Raman images and FDTD simulations of nanotriangle and nanohole arrays substrates, which clearly demonstrate that the localization of the hot spot on these SERS substrates is significantly influenced by the ratio of diameter/periodicity (D/P). The experimental and simulation data reveal that the hot spots are located around nanotriangles (D/P = 1), characteristic of localized SPR. Decreasing the D/P ratio to 0.75-0.7 led to the creation of nanohole arrays, which promoted the excitation of a propagating surface plasmon (SP) delocalized over the metal network. The optimal SERS intensity was consistently achieved at this transition from nanotriangles to nanoholes, for every periodicity (650 nm to 1.5 μm) and excitation wavelength (633 and 785 nm) investigated, despite the presence or absence of a plasmonic band near the laser excitation. Further decreasing the D/P ratio led to excitation of a localized SP located around the rim of nanohole arrays for D/P of 0.5-0.6, in agreement with previous reports. In addition, this manuscript provides the first evidence that the hot spots are positioned inside the hole for D/P of 0.4, with the center being the region of highest electric field and Raman intensity. The compelling experimental evidence and FDTD simulations offer an overall understanding of the plasmonic properties of nanohole arrays as SERS and SPR sensors, which is of significant value in advancing the diversity of applications from such surfaces.