Arbitrary Locations Research Articles

Investigation on AA7075 and AA7075/SiC surface composites using friction stir processing: An experimental and numerical approach

Friction Stir Processing, commonly known as FSP, is an innovative technique to refine microstructures and produce surface composites without any inherent defects. The heat generated during the FSP is primarily contributed by plastic deformation and edge friction which subsequently impacts the microstructure and the processed sample’s properties. In this article, FSP was performed at a tool stirring speed of 1000 rpm and 40 mm/min traveling speed. The temperature profile was obtained at arbitrary locations for AA7075 with and without Silicon Carbide (SiC). Channel and hole techniques were deployed to compare the temperature using type K thermocouples at three locations. It was found that the channel method has higher temperature values (Tp) than the hole method for both AA7075 and AA7075/SiC, whereas the Tp values for AA7075/SiC composites were found to be lowered than processed AA7075. Microstructure, mechanical, and corrosion properties were assessed for the AA7075 and AA7075/SiC. The interlayer difference between the processed and the unprocessed region has adverse effects on tensile strength. In contrast, the hardness and corrosion resistance improvement was accounted due to the uniform dispersion and pinning action of SiC. Thermo-mechanical modelling was carried out to simulate the temperatures at the plunging phase and was found to be in accordance with experimental results.

Accelerating low-frequency ground motion simulation for finite fault sources using neural networks

SUMMARYIn the context of early emergency response to moderate and large earthquake shaking, we present a simulation based low-frequency ground motion estimation workflow that expedites an existing simulation method while taking into account simplified source process information. We focus on using source information that can be expected to be available shortly after an impacting earthquake, for example moment-tensor and simple finite-fault parameters. We utilize physics-based simulations which can include effects based on source orientation or finite faults, like rupture directivity. In order to keep the computational effort within feasible bounds and to apply the approach on global scale, we restrict ourselves to a low-frequency setup (standard 1-D layered earth model and 2 Hz sampling frequency) for either a moment tensor or a simple kinematic finite fault model. From the simulated records we then extract ground motion parameters of interest for arbitrary locations within the area of expected impact and display the expected spatial patterns of ground motion. Although simulations are kept simple, the results from this low-frequency ground motion parameter simulation (e.g. for peak-ground displacement) are in good agreement with observations from two well-studied earthquakes and partially more accurate than traditional, more empirical approaches (standard deviation <0.3 log10 units). However, waveform calculation and subsequent ground motion parameter extraction is computationally expensive. For a significant computational speedup in the context of rapid ground motion assessment, we directly train neural network (NN) models from large sets of source model information and their corresponding spatial ground motion distribution. We show that the trained NNs are able to reproduce the earthquake source related effects, like directivity and focal mechanism patterns, of the ground motion in any case. Given a set of source parameters, we obtain prediction errors smaller than 0.05 log10 units (ca. 11 per cent) and a magnitude dependent increase in computational speed of more than 1000 times compared to the initial waveform modelling. The proposed procedure enables thus to immediately compute probabilistic ground motion maps related to uncertainties in source parameters estimates, for example by sampling distributions based on parameter uncertainties or directly from an existing ensemble of focal parameter solutions.

General Outage Probability Model for UAV-to-UAV links in Multi-UAV Networks

Unmanned Aerial Vehicles (UAVs) swarms have become increasingly ubiquitous in the civilian domains due to their maneuverability and scalability in collaborative flying missions. However, there is a lack of characterization of wireless communication performance in multi-UAV system without being constrained by the node spatial distributions. In this paper, the performance of a UAV swarm network is analyzed by characterizing the effects of the UAV-to-UAV (U2U) interference in terms of the Signal-to-Interference-plus-Noise Ratio (SINR). To this end, a closed-form analytical model for the Cumulative Distribution Function (CDF) of the SINR is derived by considering both deterministic and stochastic channel processes, as well as deterministic UAV mobilities. The derived model can be used to analyze U2U interference in a UAV swarm network for any arbitrary node locations. Using this model, the effects of the network parameters on various network Key Performance Indicators (KPIs) such as the outage probabilities and channel capacity rate are studied. The model is extended to incorporate hybrid LoS channels, and the general model is used to evaluate the temporal evolutions of network outage probability given the UAV trajectories. With this, the main advantage of the model in analyzing the baseline outage probabilities of multi-UAV deployments is showcased.

Fat Pointers for Temporal Memory Safety of C

Temporal memory safety bugs, especially use-after-free and double free bugs, pose a major security threat to C programs. Real-world exploits utilizing these bugs enable attackers to read and write arbitrary memory locations, causing disastrous violations of confidentiality, integrity, and availability. Many previous solutions retrofit temporal memory safety to C, but they all either incur high performance overhead and/or miss detecting certain types of temporal memory safety bugs. In this paper, we propose a temporal memory safety solution that is both efficient and comprehensive. Specifically, we extend Checked C, a spatially-safe extension to C, with temporally-safe pointers. These are implemented by combining two techniques: fat pointers and dynamic key-lock checks. We show that the fat-pointer solution significantly improves running time and memory overhead compared to the disjoint-metadata approach that provides the same level of protection. With empirical program data and hands-on experience porting real-world applications, we also show that our solution is practical in terms of backward compatibility---one of the major complaints about fat pointers.

Modeling Vehicle Flocking in Lane-Free Automated Traffic

In automated lane-free traffic, vehicles can choose any arbitrary lateral location. This enables vehicle flocking where, compared to platooning, the grouping of vehicles is possible with smaller space gaps, not only longitudinally but also laterally. Vehicle flocking can fulfill several purposes, such as increasing the road capacity, saving energy by reducing the aerodynamic drag force, and dampening shockwaves. Within this paper, we develop a control framework for modeling vehicle flocks in automated lane-free traffic. The proposed control algorithm considers two types of agents: [Formula: see text] -agents representing potential flock mates and a [Formula: see text] -agent representing the virtual leader with collective objectives (e.g., slowing down in the case of traffic congestion ahead). Our algorithm is based on energy functions for flock centering and collision avoidance, a consensus algorithm for velocity matching, and navigational feedback exerted by the virtual leader. The virtual leader’s path, which should be followed by the flock, is defined in an upper-level controller. In addition, a feedback algorithm for dynamic road boundary control is implemented. We simulate the proposed approach with very promising results. We show that vehicle flocks are efficiently formed within a few seconds, speeds are successfully aligned, and vehicle arrangements stay stable under different scenarios. In addition, the lateral and longitudinal flock extension changes with different energy functions and changing road boundaries, and vehicle flocks follow the trajectory of the virtual leader. Most importantly, vehicle flocks stay stable in the case of perturbations and the induced shock is dampened efficiently because of slight changes in the vehicles’ lateral locations.

Depth map continuous super-resolution with local implicit guidance function

Depth super-resolution (SR) is an effective approach to compensate the resolution gap between the relative low resolution of current depth sensing devices and the increasing demands of high-resolution content in many nowadays applications and future scenarios. However, most convolutional neural networks (CNNs) for depth SR are designed for particular integer SR ratios ( e.g., 2×, 4×, or 8×) or their combinations, which limits its practical applications that usually demands fractional SR ratios. This paper proposes a depth map continuous SR (DCSR) framework that is able to achieve resolution adaptation at arbitrary SR ratios. Specifically, we proposed an encoder with a dual-stream architecture. Using depth map and the guided color image as input, each stream interacts with the other by a series of adaptive resize blocks (ARBs) to retain essential details and resize stabilization across features of various resolutions. In the decoder, depth information at arbitrary missing locations is fitted as the weighted prediction of neural implicit functions (NIFs) from latent codes containing relative coordinate, target pixel size, and fused depth-color features. Extensive experiments demonstrate that the proposed DCSR method provides high quality depth SR results at arbitrary ratios, which is a promising merit for practical applications. Code will be released upon the publication of this work.

Система мониторинга и анализа распределенных параметров и пожарная безопасность «Умного дома»

Система мониторинга и анализа распределенных параметров и пожарная безопасность «Умного дома»

Honey bees infer source location from the dances of returning foragers

Honeybees (Apis mellifera carnica) communicate the direction and distance to a food source by means of a waggle dance. We ask whether bees recruited by the dance use it only as a flying instruction, with the technical form of a polar vector, or also translate it into a location vector that enables them to set courses directed toward the food source from arbitrary locations within their familiar territory. The flights of recruits captured on exiting the hive and released at distant sites were tracked by radar. The recruits performed first a straight flight in approximately the compass direction indicated by the dance. However, this "vector" portion of their flights and the ensuing tortuous "search" portion were strongly and differentially affected by the release site. Searches were biased toward the true location of the food and away from the location specified by translating the origin for the danced polar vector to the release site. We conclude that by following the dance recruits get two messages, a polar flying instruction (bearing and range from the hive) and a location vector that enables them to approach the source from anywhere in their familiar territory. The dance communication is much richer than thought so far.

Estimation of the selected treatment mean in two stage drop-the-losers design

ABSTRACT A common problem faced in clinical studies is that of estimating the effect of the most effective (e.g. the one having the largest mean) treatment among k ( ≥ 2 ) available treatments. The most effective treatment is adjudged based on numerical values of some statistic corresponding to the k treatments. A proper design for such problems is the so-called “Drop-the-Losers Design (DLD)”. We consider two treatments whose effects are described by independent Gaussian distributions having different unknown means and a common known variance. To select the more effective treatment, the two treatments are independently administered to n 1 subjects each and the treatment corresponding to the larger sample mean is selected. To study the effect of the adjudged more effective treatment (i.e. estimating its mean), we consider the two-stage DLD in which n 2 subjects are further administered the adjudged more effective treatment in the second stage of the design. We obtain some admissibility and minimaxity results for estimating the mean effect of the adjudged more effective treatment. The maximum likelihood estimator is shown to be minimax and admissible. We show that the uniformly minimum variance conditionally unbiased estimator (UMVCUE) of the selected treatment mean is inadmissible and obtain an improved estimator. In this process, we also derive a sufficient condition for inadmissibility of an arbitrary location and permutation equivariant estimator and provide dominating estimators in cases, where this sufficient condition is satisfied. The mean squared error and the bias performances of various competing estimators are compared via a simulation study. A real data example is also provided for illustration purpose.

Economic model predictive control with terminal set dynamic programming for tracking control

AbstractThis paper focuses on vehicle tracking control issues with consideration of energy efficiency, ride comfort and tracking performance. To address this issue, an economic model predictive control (EMPC) framework is proposed by taking average performance into account and introducing a time‐varying terminal set. We integrate an economic model predictive controller and a terminal controller with a feedback gain related to the time‐varying terminal set into the proposed EMPC framework. An acceleration‐dependent average constraint is designed and incorporated into the MPC optimization problem to facilitate the convergence of the actual acceleration to the desired one, which enables the vehicle to implement a smooth driving style that boosts energy economy. A tuning factor in the average constraint has the capacity to balance energy consumption and control performance. Under the premise of invariance constraints, a dynamic terminal set is constructed by solving a dynamic programming problem online, which enables an arbitrary location and scale of the terminal set at each iteration by taking the current and predicted tracking errors into account. This allows a reduction in the conservativeness of an economic model predictive controller in the sense of both the region of attraction and the cost bound. Recursive feasibility of the MPC optimization problem and the terminal set dynamic programming is ensured, and average performance is not worse than the performance with an optimal steady‐state operation. Moreover, the convergence of the closed‐loop tracking error to the optimal steady‐state is guaranteed by using the dissipativity theory. The effectiveness of the proposed algorithm is verified by numerical comparisons with different controller parameters and standard EMPC.

A stochastic framework for computationally efficient fail-safe topology optimization

Fail-safe robustness is an important design philosophy for critical structural systems such as airframes. The basic idea of fail-safe design is that a structure should be designed to survive normal loading conditions when local damage occurs. In the context of topology optimization, fail-safe consideration innovates the morphogenesis for structural design in addition to the parametric safety margin. Existing fail-safe topology optimization methods usually enumerate all/predefined possible damages among the design domain and optimize the worst-damage scenario. However, virtually all damages can occur and cause the structural system to stop functioning. This work proposes the Stochastic Fail-Safe Topology Optimization (S-FSTO) for computationally viable fail-safe topology optimization which considers all possible damages according to the associated severity, including the worst-damage scenario. Critical damages for density value updates are sampled through the proposed two-level sampling strategy, which allows arbitrary size and location of damages. A design domain segmentation strategy is proposed to improve the sampling efficiency. The required number of FEA runs could be reduced by multiple orders of magnitudes. The proposed S-FSTO could be conveniently equivalent to a variety of existing schemes by customizing the proposal distributions of the two-level sampling strategy. The dependence on subjective decisions for selecting local damages could be minimized. The proposed framework has been evaluated for the design of cantilever beams and airplane bearing brackets. The generated conceptual designs are significantly more robust than the deterministic ones when local damage occurs. For the design of cantilever beams, S-FSTO produced designs with similar performance as that from the original FSTO and saved 99.4% FEA runs.

Analysis of MC Systems Employing Receivers Covered by Heterogeneous Receptors

This paper investigates the channel impulse response (CIR), i.e., the molecule hitting rate, of a molecular communication (MC) system employing an absorbing receiver (RX) covered by multiple non-overlapping receptors. In this system, receptors are heterogeneous, i.e., they may have different sizes and arbitrary locations. Furthermore, we consider two types of transmitter (TX), namely a point TX and a membrane fusion (MF)-based spherical TX. We assume the point TX or the center of the MF-based TX has a fixed distance to the center of the RX. Given this fixed distance, the TX can be at different locations and the CIR of the RX depends on the exact location of the TX. By averaging over all possible TX locations, we analyze the expected molecule hitting rate at the RX as a function of the sizes and locations of the receptors, where we assume molecule degradation may occur during the propagation of the signaling molecules. Notably, our analysis is valid for different numbers, a wide range of sizes, and arbitrary locations of the receptors, and its accuracy is confirmed via particle-based simulations. Exploiting our numerical results, we show that the expected number of absorbed molecules at the RX increases with the number of receptors, when the total area on the RX surface covered by receptors is fixed. Based on the derived analytical expressions, we compare different geometric receptor distributions by examining the expected number of absorbed molecules at the RX. We show that evenly distributed receptors result in a larger number of absorbed molecules than other distributions. We further compare three models that combine different types of TXs and RXs. Compared to the ideal model with a point TX and a fully absorbing RX, the practical model with an MF-based TX and an RX with heterogeneous receptors yields a lower peak CIR, suffers from more severe inter-symbol interference, and gives rise to a higher average bit error rate (BER). This underlines the importance of our analysis of practical TX-RX models since the existing CIR and BER analyses based on the ideal model do not reflect the performance achievable in practice. Numerical results show that different vesicle generation rate results in the same number of molecules harvested by the TX, but a different peak received signal at the RX.

A Planar Orbicular Rectenna Array System With 3-D Uniform Coverage for Wireless Powering of IoT Nodes

Microwave power transfer (MPT) is a revolutionary technique for charging batteries of wireless sensor nodes in smart applications. However, sensor nodes can be positioned at any arbitrary orientation and location with respect to the microwave transmitter (Tx). Therefore, harvested DC power depends on the node’s position and orientation. Thus, to reduce this reliance, a novel, fully integrated planar multisector rectenna (Rx) array is designed to achieve a nearly uniform 3-D spherical DC coverage. To realize orientation insensitive azimuth and elevation plane coverage, the proposed Rx features eight radially arranged endfire Rx (EFR-antenna) elements, and a bore-sight Rx (BSR-antenna) element with multiarms for inherent DC combining is used at the center with orthogonally polarized ports. Furthermore, direct conjugate matching of antenna and rectifier circuit with integrated operation is applied to realize a fully integrated design. This reduces insertion losses and achieves the desired 3-D coverage along with miniaturization, shaping it suitable for deployment at space-constrained IoT sensor nodes for orientation oblivion wireless powering.

Competitive perimeter defense with a turret and a mobile vehicle

We consider perimeter defense problem in a planar conical environment with two cooperative heterogeneous defenders, i.e., a turret and a mobile vehicle, that seek to defend a concentric perimeter against mobile intruders. Arbitrary numbers of intruders are released at the circumference of the environment at arbitrary time instants and locations. Upon release, they move radially inwards with fixed speed towards the perimeter. The defenders are heterogeneous in terms of their motion and capture capabilities. Specifically, the turret has a finite engagement range and can only turn (clockwise or anti-clockwise) in the environment with fixed angular rate whereas, the vehicle has a finite capture radius and can move in any direction with unit speed. We present a competitive analysis approach to this perimeter defense problem by measuring the performance of multiple cooperative online algorithms for the defenders against arbitrary inputs, relative to an optimal offline algorithm that has information about the entire input sequence in advance. Specifically, we establish necessary conditions on the parameter space to guarantee finite competitiveness of any online algorithm. We then design and analyze four cooperative online algorithms and characterize parameter regimes in which they have finite competitive ratios. In particular, our first two algorithms are 1-competitive in specific parameter regimes, our third algorithm exhibits different competitive ratios in different regimes of problem parameters, and our fourth algorithm is 1.5-competitive in specific parameter regimes. Finally, we provide multiple numerical plots in the parameter space to reveal additional insights into the relative performance of our algorithms.

Image formation by two plane mirrors

We revisit the problem of image formation of a point object by two plane mirrors meeting at a convex angle θ. Although a complete solution to the problem already exists in the literature, the simple formula is often assumed to be the universal formula that counts the number of images, irrespective of θ or the location of the object. A survey, involving both school students and teachers, shows that the simple formula in conjunction with rounding off to the closest integer(s) is still widely thought of as the correct way to count the number of images formed. In order to address this rampant misconception, we rederive the correct formula for an arbitrary mirror angle θ and arbitrary location of the object in an elementary way. The proof is easily communicable to high school students. We justify the formula using a physical setup and capturing real-life images. Finally, we provide a simulation written in an open source software GeoGebra as an additional visual aid in understanding the problem and its solution.

A convenient and stable graph-based pressure estimation methodology for water distribution networks: Development and field validation

Accurate estimation of unknown nodal pressures (nodal heads) is necessary for efficient operation and management of water distribution networks (WDNs), but existing methods such as hydraulic simulation and data interpolation can hardly reconcile estimation accuracy with model construction and maintenance costs. Recent developments in graph signal processing (GSP) techniques provide us with new tools to utilize information in WDN hydraulics and available measurements. In a pilot study, a graph-based head reconstruction (GHR) method was proposed, which used GSP to reconstruct the spatially slow-varying parts of nodal heads from a limited number of field measurements to approximate original heads. GHR has illustrated the effectiveness and ease of implementation of GSP-based methods. However, due to the ill-conditioning reconstruction process and inherent uncertainties, GHR may show unstable results with large errors if pressure meters are not installed at specific optimized locations, which limits its applicability. To solve this problem and discover a stable and convenient method that can support a wider range of applications, a graph-based head reconstruction method with improved stability (GHR-S) is proposed. GHR-S utilizes a rough estimation of unknown pressures as pseudo measurements, which provide additional constraints and avoid the occurrence of unreasonable results during the reconstruction process. A middle-sized network with synthetic data illustrates the stability, convenience, and accuracy of GHR-S with arbitrary meter locations and uncalibrated model parameters. GHR-S is also applied to a large real-life network with field measurements, and successfully estimates the unknown pressures of 83,000 nodes with only 58 measurements, showing its effectiveness in practical engineering.

An approach to modeling vibrations of systems composed of beams, rigid bodies, and point masses

An approach for vibration analysis of three-dimensional motion beam systems is formulated. The proposed method employs analytical solutions that are used to formulate a unified, three-dimensional dynamic representation the elements of beam systems, including beams, rigid bodies, and point masses. Interconnections between system’s components and their connections to the inertial frame are formulated as motion constraints. The interconnections can be rigid or flexible and can be located at arbitrary locations on the system components. The unified representations of different types of system elements and of different interconnection allows vibration analysis of complex beam systems. A procedure is developed for computation of natural frequencies and mode shapes by employing a sequence of orthogonal transformations. A three-dimensional structure that includes flexibly and rigidly connected beams and rigid bodies with different types of connections, is used to demonstrate the capabilities of the proposed method. The accuracy of the approach is verified by restricting the structure to planar motion with rigid connections and comparing the results to results of obtained in previous studies. The example structure is used to demonstrate the ability of the proposed approach to conduct vibrational analysis study of three-dimensional structures with different boundary conditions. Moreover, it also demonstrates suitability of the approach for studying sensitivity of vibrations characteristics, such as modal frequencies, with respect to system parameters, e.g. interconnections stiffness.

Investigating underground water salinity in east coastline of Tamil Nadu, India and improving its quality through solar assisted desalination

The gradual infiltration of sea water into the ground near coastal regions causes severe damage to the quality of underground water. It will end up with a high level of salinity in the bore wells near the coastal areas. In this study, an assessment has been conducted systematically to analyse the water quality parameters and level of salinity in underground water samples, which were collected from the sub-urban area near the coastal line of Chennai, a metropolitan city in Tamil Nadu. The various factors pertaining to the water quality were examined with the water samples collected from eight arbitrary locations, and the results show that the intrusion of seawater is predominant for the salinity of the underground water in this zone. In order to provide a low-cost solution for producing potable water, an effective solar assisted desalination method using a solar desalting still (SDS) has been proposed. The improvement in the water quality parameters of the samples after the solar distillation process was critically investigated. The outcomes evidenced that the treatment of salty underground water with the aid of SDS has been effectively enhanced its quality for the domestic uses.

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

Assessment of underground water quality and water quality index across the Noyyal River basin of Tirupur District in South India

The quality of underground water is essential for ensuring the long-term, secure use of this resource for any activity, especially drinking, irrigation, and so on. However, the country's rapid urbanization and industrialization have frequently resulted in groundwater contamination as a result of the discharge of unprocessed industrial effluents and municipal wastewater into the river. Tirupur is an important city in south India, known for its textile industries and diverse culture. It is rich in textile processing mills and located on the bank of the Noyyal River. The underground water quality across the Noyyal basin was assessed in this study by taking underground water samples from fifteen arbitrary locations in Tirupur along the Noyyal River's downstream. Several indicators of water quality have been taken into account in this analysis, including hydrogen potential (pH), total dissolved solids, total hardness, calcium, magnesium, electrical conductivity, dissolved oxygen, total alkalinity, chlorides, nitrates, bicarbonates, and sulfates. The underground water quality index (UWQI) has also been computed based on the test results. The outcomes indicate that underground water quality has been significantly affected due to the contaminated Noyyal River. To conserve the quality of the underground water, an appropriate action plan needs to be executed.