Array Reference Research Articles

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

Abstract The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

Tilted Fiber Bragg Grating Measurements During Laser Ablation of Hepatic Tissues: Quasi-Distributed Temperature Reconstruction and Cladding Mode Resonances Analysis

In this work, we investigate the application of tilted fiber Bragg grating (TFBG) sensors during <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i> laser ablation of porcine hepatic tissues. Initially, TFBG’s ability to measure the surrounding refractive index (RI) for different sucrose concentrations and the possibility to measure the RI of the targeted tissue during laser ablation (LA) is analyzed. After, the temperature sensing modality of TFBG is investigated in detail. We have implemented an algorithm for quasi-distributed spatial temperature profile reconstruction along TFBG. The algorithm models the TFBG core mode spectrum as a chain of Bragg gratings (each Bragg grating is modeled <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">via</i> coupled mode theory), where each grating is sensitive to local temperature changes. After, the Gaussian-shape temperature profile along the TFBG is reconstructed using the iterative optimization technique. Temperature measurements have been compared with highly-dense FBG array measurements and with conventional TFBG point temperature measurements based on the core mode tracking techniques (maximum tracking, X-dB Bandwidth, centroid methods). Overall, the proposed reconstruction algorithm is able to provide a quasi-distributed temperature profile along TFBG, which is not possible to obtain using conventional point temperature measurements based on the TFBG’s core mode tracking. The resulted root-mean-square error in comparison to FBG array reference measurements is 7.8±1.7 °C. In general, the results show that the main reliable sensing modality of TFBG during LA is temperature monitoring, which can be significantly improved by the proposed algorithm.

Acoustic Shock Formation in Noise Propagation During Military Aircraft Ground Run-Up Operations

A distinctive feature of many high-amplitude jet noise waveforms is the presence of acoustic shocks. Metrics indicative of shock presence, specifically the skewness of the time derivative of the waveform, the average steepening factor, and a new wavelet-based metric called the shock energy fraction, are used to quantify the strength and prevalence of acoustic shocks within waveforms recorded 10–305 m from a tethered military aircraft. The derivative skewness is more sensitive to the presence of the largest and steepest shocks, whereas the average steepening factor and shock energy fraction tend to emphasize aggregate behavior of the entire waveform. These metrics are applied at various engine conditions, over a wide range of angles and distances, to assess the growth and decay of shock waves. This paper represents the first time that the development of these metrics is shown from the near field to the far field, out to 305 m. The responses of these metrics point to significant shock formation occurring through nonlinear propagation out to 76 m from the microphone array reference position. Although these strongest shocks decay past 35 m, continued shock formation and atmospheric absorption can make the steepened nature of the waveform more prominent out to 305 m.

Novel fuzzy-assisted nonlinear optimal power generation method for grid-connected SPV system with TLBO optimisation

This research article presents a novel fuzzy-assisted nonlinear proportional-integral (f-NPI) controller based optimal power generation method for a 100 kW grid-connected solar photovoltaic (SPV) system with boost converter topology. The primary objective is to optimise power generation when variations in irradiance and temperature are experienced. f-PI and novel f-NPI based PV array reference current predictor is implemented to adjust the duty cycle for the converter. The gain parameters of controllers are being fairly tuned using teaching-learning based optimisation (TLBO) technique. A comprehensive simulation analysis is carried out using MATLAB R2017a, which verifies that the utilisation of primitive parameters, i.e., irradiance and temperature for the proposed controller exhibits enhanced performance in comparison to extant P&O and fuzzy logic controller (using secondary/conventional parameters like voltage and current) in terms of settling time, efficiency and THD. Moreover, the operation of the novel f-NPI based method is found to comply with IEEE 929 standard.

Novel fuzzy-assisted nonlinear optimal power generation method for grid-connected SPV system with TLBO optimisation

This research article presents a novel fuzzy-assisted nonlinear proportional-integral (f-NPI) controller based optimal power generation method for a 100 kW grid-connected solar photovoltaic (SPV) system with boost converter topology. The primary objective is to optimise power generation when variations in irradiance and temperature are experienced. f-PI and novel f-NPI based PV array reference current predictor is implemented to adjust the duty cycle for the converter. The gain parameters of controllers are being fairly tuned using teaching-learning based optimisation (TLBO) technique. A comprehensive simulation analysis is carried out using MATLAB R2017a, which verifies that the utilisation of primitive parameters, i.e., irradiance and temperature for the proposed controller exhibits enhanced performance in comparison to extant P&O and fuzzy logic controller (using secondary/conventional parameters like voltage and current) in terms of settling time, efficiency and THD. Moreover, the operation of the novel f-NPI based method is found to comply with IEEE 929 standard.

Simplified calibration method for multibeam footprint displacements due to non-concentric arrays

When the offset between the transmitter and the receiver in the multibeam is large, neglecting the offset will introduce depth errors into the multibeam footprints. Although the current non-concentric algorithm (NCCA) considers this offset, its model is complicated and time-consuming. To solve the issues, a simplified method is developed. First, the offset is considered by constructing two separated intersecting triangles projected by the transmitted and received cones under the array reference frame (ARF); second, two groups of the footprint coordinates under the ARF are calculated with slant ranges from the transmitter and receiver to the footprint, respectively; then, the transmitted and received vectors, and their corresponding one-way travel times (OWTTs) are calculated by the two coordinates; finally, an iteration is used to adjust the two slant ranges according to the measured and the calculated time, and the optimal location of the footprint will be obtained. To verify the proposed method, comparisons between existing methods and ours are made. The results indicate that when the depth is about 457 m, the average depth deviation between the NCCA and ours is only 0.03 m. And our new method saves about 17% of computation time compared to that of the NCCA.

1-bit Massive MU-MIMO Precoding in VLSI

Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in fifth-generation (5G) wireless systems as it offers significant improvements in spectral efficiency compared to existing multi-antenna technologies. The presence of hundreds of antenna elements at the base station (BS), however, results in excessively high hardware costs and power consumption, and requires high interconnect throughput between the baseband-processing unit and the radio unit. Massive MU-MIMO that uses low-resolution analog-to-digital and digital-to-analog converters (DACs) has the potential to address all these issues. In this paper, we focus on downlink precoding for massive MU-MIMO systems with 1-bit DACs at the BS. The objective is to design precoders that simultaneously mitigate MU interference and quantization artifacts. We propose two nonlinear 1-bit precoding algorithms and corresponding very large-scale integration (VLSI) designs. Our algorithms rely on biconvex relaxation, which enables the design of efficient 1-bit precoding algorithms that achieve superior error-rate performance compared with that of linear precoding algorithms followed by quantization. To showcase the efficacy of our algorithms, we design VLSI architectures that enable efficient 1-bit precoding for massive MU-MIMO systems, in which hundreds of antennas serve tens of user equipments. We present corresponding field-programmable gate array (FPGA) reference implementations to demonstrate that 1-bit precoding enables reliable and high-rate downlink data transmission in practical systems.

Rift–plume interaction reveals multiple generations of recycled oceanic crust in Azores lavas

We present 176Hf/177Hf isotope ratios on 41 previously well-characterized subaerial and submarine samples from the Azores islands of São Miguel, Terceira, Graciosa, Faial, Pico and the João de Castro seamount (on the Terceira Rift). In εNd–εHf isotope space all Azores lavas fall below the mantle array reference line and do not overlap the proximal Atlantic MORB. Lavas from São Miguel and João de Castro form two distinct and well defined arrays extending below the mantle array, which has not been previously documented in other oceanic magmatic provinces. The Nd-Hf isotope compositions of João de Castro overlap those of HIMU type lavas, yet they lack the characteristically radiogenic Pb isotope ratios of HIMU. The combined Nd-Hf-Pb-Sr isotope systematics of both São Miguel and João de Castro endmembers can be explained by recycling of a single package of heterogeneous oceanic crust ranging from D-MORB to E-MORB in composition, with an age between 2.5 and 3.0Ga, with no requirement for parent-daughter ratio modification during subduction. In contrast the Nd-Hf-Pb isotope systematics of lavas from São Jorge, Terceira, Graciosa, Pico and Faial are consistent with the presence of younger (<700Ma) recycled crust that underwent low-temperature alteration and dehydration during subduction. There is no evidence in the erupted lavas for direct mixing between these two generations of recycled material within the plume. These data suggest that old recycling age and absence of sediments along with recycled oceanic crust are both required to develop isotopic compositions below the mantle array in εNd–εHf space. Our modeling shows that the compositional variability of erupted MORB is large enough that, given enough time, they can generate a wide range of isotope compositions such as observed in OIB. Lastly, lava compositions along the Terceira rift can be explained by a westward asthenospheric flux along a tilted lithosphere/asthenosphere boundary, where fertile components are exhausted by partial melting after ∼70km of transport along the Terceira Rift. While this observation is broadly consistent with the plume source–ridge sink model, it also suggests that the lithosphere/asthenosphere boundary geometry can smear the view of the plume heterogeneity.

Selection and validation of reliable reference genes for RT-qPCR analysis in a large cohort of pituitary adenomas

BackgroundReal-time reverse transcription quantitative PCR (RT-qPCR) has become the method of choice for quantification of gene expression changes. The most important limitations of RT-qPCR are inappropriate data normalization and inconsistent data analyses. Pituitary adenomas are common tumours, and the appropriate interpretation of increasingly published data within this field is prevented by the lack of a proper selection and validation of stably expressed reference genes. AimTo find and validate the optimal reference gene or gene combination for reliable RT-qPCR gene expression in both non-functioning (NFPA) and hormone secreting (GH and ACTH) pituitary adenomas. Material and methodsThirty commonly used reference genes (PCR array reference gene panel, BioRad, Hercules, CA) were quantified by RT-qPCR in 24 pituitary adenomas (12 NFPA, 8 GH and 4 ACTH). The data was analysed using three programs: geNorm (Qbase+), Normfinder and BestKeeper having different algorithms to identify the most stable reference gene or combination of reference genes. Three reference genes ALAS1, PSMC4 and GAPDH, were selected for further validation in a larger cohort of 223 adenomas (141 NFPA, 63 GH and 19 ACTH). ResultsIn all adenomas, ALAS1 and PSMC4 were the most stable reference genes as estimated by geNorm and Normfinder, whereas Bestkeeper ranked RPLP0 and ACTB as the two most stable out of 10 carefully selected genes. The best gene combination was PSMC4 and ALAS1 (geNorm) or PSMC4 and GAPDH (Normfinder). The validation experiment (geNorm) showed that the most stable gene combinations were ALAS1 and GAPDH in NFPA, and PSMC4 and GAPDH in hormone secreting adenomas. ConclusionsSeveral of the reference genes expressed good stability yielding several candidate genes. PSMC4 and ALAS1 were overall the most stably expressed genes in pituitary adenoma merely differing in ranking order. PSMC4 and ALAS1 have so far not been reported as reference genes in pituitary adenomas. The various reference gene algorithms showed a mixed selection of top ranked genes, thus suggesting a need for an individualised and rational choice of reference genes.

Global load instruction aggregation based on dimensions of arrays

Most modern processors have some cache memories that are much faster than main memory. These cache memories function well if temporal or spatial localities in programs are enhanced; therefore, the continuous accesses to the same array that improves the localities can enhance effective utilization of the cache memories. In addition, because a multidimensional array can be regarded as an array of lower dimensional arrays, the continuous accesses to array references with the most similar indexes can enhance the utilization of them further. We propose a new code motion algorithm called MDGLIA that improves utilization of cache memory. MDGLIA moves each array reference immediately after the preceding references accessing the same array with the most similar indexes, and then delays it as late as possible without changing the access order. These two-step code motions contribute to not only improvement of the cache efficiency in the overall program but also suppression of register pressure. We implemented MDGLIA in a real compiler and evaluated it for matrix multiplication and SPEC benchmarks. The experimental results show that our algorithm reduces the number of cache misses in most cases.

REAL TIME IMPLEMENATION FOR DOA ESTIMATION METHODS ON NI-PXI PLATFORM

In this paper, we present flve difierent approaches to estimate direction of arrival (DOA) of multiple incident RF sources. The proposed methods are based on extracting the signal and noise subspaces from the Q matrix, R matrix, or both Q and R matrices of the QR decomposed received data matrix. The angle of the signal arrival is extracted from the signal subspace by using similar techniques as employed by MUSIC and ESPRIT methods. The simulation results are shown which verify accurate DOA estimates for both single and two sources. In addition, an experimental veriflcation of the proposed methods is also presented. The methods are implemented in LabVIEW software and a prototype is built using National Instruments (NI) hardware. Furthermore, the details of experimental procedures are presented which includes interfacing the uniform linear array (ULA) of antennas with the NI-PXI platform, phase difierence calibration between the RF receivers, and selection of transmitter and receiver parameters. The experimental results are shown for a single and two RF sources lying at arbitrary angles from the array reference, which verify the successful real-time implement-ability of the proposed DOA estimation methods.

Passive source localization using RROA based on eigenvalue decomposition algorithm in WSNs

When in WSNs sensors receive different noise intensities or the wireless transmission channel has the shadow fading effect, the association metrics estimation method for range ratios of arrival (RROA) and the passive source localization algorithm based on RROA are studied. Firstly, the eigenvector decomposition (EVD) approach is used to estimate the RROA association metrics. The noise intensity received by each sensor can be estimated by performing EVD on the covariance matrix of the received signal. Secondly, by rotating the array reference point at each of the array sensors, a number of covariance matrices are constructed and the EVD approach can be used to cancel the shadow fading effect. Thus RROA association metrics can be estimated reliably. Finally, the weighted-least-squares (WLS) algorithm based on the RROA association metrics is proposed. The proposed approach is robust to channel shadow fading effect and different noise intensities received.

Thick film screen printed environmental and chemical sensor array reference electrodes suitable for subterranean and subaqueous deployments

PurposeThe purpose of this paper is to report thick film environmental and chemical sensor arrays designed for deployment in both subterranean and submerged aqueous applications.Design/methodology/approachVarious choices of materials for reference electrodes employed in these different applications have been evaluated and the responses of the different sensor types are compared and discussed.FindingsResults indicate that the choice of binder materials is critical to the production of sensors capable of medium term deployment (e.g. several days) as the binders not only affect the tradeoff between hydration time and drift but also have a significant bearing on device sensitivity and stability. Sensor calibration is shown to remain an issue with long‐term deployments (e.g. several weeks) but this can be ameliorated in the medium term with the use of novel device fabrication and packaging techniques.Originality/valueThe reported results indicate that is possible through careful choice of materials and fabrication methods to achieve near stable thick film reference electrodes that are suitable for use in solid state chemical sensors in a variety of different application areas.

Array dataflow analysis for polyhedral X10 programs

This paper addresses the static analysis of an important class of X10 programs, namely those with finish/async parallelism, and affine loops and array reference structure as in the polyhedral model. For such programs our analysis can certify whenever a program is deterministic or flags races. Our key contributions are (i) adaptation of array dataflow analysis from the polyhedral model to programs with finish/async parallelism, and (ii) use of the array dataflow analysis result to certify determinacy. We distinguish our work from previous approaches by combining the precise statement instance-wise and array element-wise analysis capability of the polyhedral model with finish/async programs that are more expressive than doall parallelism commonly considered in the polyhedral literature. We show that our approach is exact (no false negative/positives) and more precise than previous approaches, but is limited to programs that fit the polyhedral model.

HARDWARE IMPLEMENTATION OF A PROPOSED QR-TLS DOA ESTIMATION METHOD AND MUSIC, ESPRIT ALGORITHMS ON NI-PXI PLATFORM

In this paper, we present an experimental veriflcation of a novel QR-TLS algorithm. Two other algorithms for direction of arrival (DOA) estimation of multiple incident source signals called multiple signal classiflcation (MUSIC) and estimation of signal parameters via rotational invariance techniques (ESPRIT) are implemented on a National Instruments (NI) PXI platform. The proposed method is based on subspace decomposition of a received data into a signal and a noise space using QR decomposition. The angle of the signal arrival information is extracted from the signal subspace by using the method of total least squares (TLS). The algorithms are implemented in LabView NI hardware. The experimental procedures are discussed in details which includes interfacing of the uniform linear array (ULA) of antennas with the NI-PXI platform, calibrating phase difierences between the RF receivers, and selecting transmitter and receiver parameters, for determining the DOAs of the multiple incident source signals. The experimental results are shown for a single and two sources lying at arbitrary angles from the array reference to verify the successful real time implementation of the proposed and other DOA estimation algorithms.

Source Localization Using Sparse Large Aperture Arrays

In this paper, a novel source/target localization approach is proposed using a number of sensors (surrounding or not surrounding one or more sources) to form a sparse large aperture array of known geometry. Under a large array aperture, the array response (manifold vector) obeys a spherical wave rather than a plane wave propagation model. By rotating the array reference point to be at each of the array sensors, a number of covariance matrices are constructed. It is shown that the eigenvalues of these covariance matrices are related to the source location with respect to the array reference point. The proposed approach is robust to channel fading and considers both wideband and narrowband assumptions. The performance of the proposed approach is evaluated via simulations as a function of array geometry, number of snapshots ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> ) and signal to noise ratio (SNR) and is shown to exceed existing techniques.

Corrosion Behaviors of 316 Stainless Steel Weldment Studied by Array Reference Electrodes

Corrosion Behaviors of 316 Stainless Steel Weldment Studied by Array Reference Electrodes

Blind Separation of Coherent Signals Based on Toeplitz Matrix Reconstruction

A new blind beamforming algorithm for separating and estimating coherent signals arriving at an antenna array is proposed in this paper. This algorithm is implemented through arranging the received data’s correlation function of each array element and reference array element (the first array element), to form the Hermitian Toeplitz matrix first. Then through the singular value decomposition of the matrix the signal subspace and noise subspace can be get, in order to achieve the direction vector of coherent sources to beamform, which can separate the independent signals from different directions effectively without knowing the transcendent knowledge of the signals. The new approach can estimate the coherent signals’ direction-of-arrival(DOA) on the basis of separation, and has good performance under the low SNR. The simulation results show that the proposed method is effective．

An Efficient Particle Filter–based Tracking Method Using Graphics Processing Unit (GPU)

Particle filter has been proven very robust in handling non-linear and non-Gaussian problems and has been widely used in the area of object tracking. One of the main problems in particle filter-based object tracking is, however, its high computational cost induced by the most time-consuming stage of measurement model computation. This paper makes progress in resolving the problem by proposing an efficient particle filter-based tracking algorithm using color information. First, a compact color cooccurrence histogram is presented, which considers both spatial and color information and can effectively represent color distribution with a very small number of histogram bins. The paper also introduces integral images by which the cooccurrence histogram can be obtained with simple array reference operations. However, the construction of the integral images on the CPU may be computationally expensive. Hence, this paper develops parallel algorithms on a desktop Graphics Processing Unit (GPU), which accomplishes the integral images construction and cooccurrence histogram computation after bin index determination. The resulting algorithm is quite efficient and has better performance than the traditional histogram-based tracking algorithm. The tracking time of the proposed algorithm increases insignificantly with the growth of particle number, and it remains consistent among varying image sequences and stable throughout all frames in the same image sequence due to its irrelevance to object size. Experiments in diverse image sequences validate our conclusions.

Implicit array bounds checking on 64-bit architectures

Several programming languages guarantee that array subscripts are checked to ensure they are within the bounds of the array. While this guarantee improves the correctness and security of array-based code, it adds overhead to array references. This has been an obstacle to using higher-level languages, such as Java, for high-performance parallel computing, where the language specification requires that all array accesses must be checked to ensure they are within bounds. This is because, in practice, array-bounds checking in scientific applications may increase execution time by more than a factor of 2. Previous research has explored optimizations to statically eliminate bounds checks, but the dynamic nature of many scientific codes makes this difficult or impossible. Our approach is, instead, to create a compiler and operating system infrastructure that does not generate explicit bounds checks. It instead places arrays inside of Index Confinement Regions (ICRs), which are large, isolated, mostly unmapped virtual memory regions. Any array reference outside of its bounds will cause a protection violation; this provides implicit bounds checking. Our results show that when applying this infrastructure to high-performance computing programs written in Java, the overhead of bounds checking relative to a program with no bounds checks is reduced from an average of 63% to an average of 9%.