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Mechanical and metallurgical behavior of double-sided friction stir welded (DS-FSW) joints of 6 mm thick magnesium alloy (AZ31B) plates, under 0° (Joint W1) and 2° (Joint W2) tool tilt angle, using scrolled shoulder and screwed pin tool were investigated for the first time. Joint fabrication using tool rotational speed of 800 rpm and welding speed of 50 mm/min resulted in tunnel defect in W1 joint and defect free W2 joint. The tensile test results show the joint efficiency of 74% for W1 joint and 87% for W2 joint. The defect free micro tensile samples extracted from first pass (FP), second pass (SP) and overlap region (OZ) of both the welds shows higher degree of grain refinement. Also, microhardness in stir zone (SZ), thermo-mechanically affected zone (TMAZ) and heat-affected zone (HAZ) of W2 joint is high compared to W1 joint. These metallurgical enhancements in each zone of 2° tilt angle joint led to the remarkable improvement in joint efficiency of FP-2 (80%), OZ-2 (71%) and SP-2 (91%) tensile specimens compared to FP-1 (76%), OZ-1 (63%) and SP-1 (67%) for W1 welded joint. Significant improvement by 26%, 19% and 32% and in percentage elongation was observed in the first pass, overlap region and second pass respectively for W2 joint over W1 joint. Scanning electron microscopy (SEM) characterization revealed ductile and shear fracture modes, wherein, larger area fraction of dimpled morphology and tearing ridges was observed for the macro and micro tensile specimens of W2 joint.

Intelligent offloading of computation-intensive tasks to a mobile cloud server provides an effective mean to expand the usability of wireless devices and prolong their battery life, especially for low-cost internet-of-things (IoT) devices. However, realization of this technology in multiple-input multiple-output (MIMO) systems requires sophisticated design of joint computation offloading and other functions such as channel state information (CSI) estimation, beamforming, and resource allocation. In this paper, we study the computation task offloading and resource allocation optimization in MIMO based mobile edge computing systems considering perfect/imperfect-CSI estimation. Our design aims to minimize the maximum weighted energy consumption subject to practical constraints on computing and radio resources and allowable latency. The optimal and low-complexity algorithms are proposed to solve the underlying mixed integer non-linear problems (MINLP). For the perfect-CSI, we employ bisection search to find the optimal solution. The low-complexity algorithms are developed by decomposing the original optimization problem into the offloading optimization (OP) and power allocation (PA) subproblems and solve them iteratively. Moreover, the difference of convex functions (DC) method is employed to deal with non-convex structure of (PA) in the imperfect-CSI scenario. Numerical results confirm the advantages of proposed designs over conventional local computation strategies in energy saving and fairness.

Sensitivities of drag and lift to body force and blowing/suction are investigated based on a continuous adjoint method through Reynolds-averaged Navier–Stokes simulation (RANS). For a Clark-Y airfo...

In this study the relationship between two families of pairwise associated functions, describing boundary wetting and drying curves, is modelled. This relationship includes both regular and random constituents, and it is represented by a limited dataset of N known pairs of these curves, which pertain to N different soils. Using the dependent domain theory of hysteresis, we show that the regular constituent in this relationship can be described by a linear integral operator that, for a given input measured boundary wetting curve, predicts its associated boundary drying curve. The operator is optimized to reduce the influence of the random scattering of the pairs of curves. The optimization of the operator is performed with respect to the given input measured boundary wetting curve using a representative calibration dataset of k (k≤N) pairs of curves, which are a part of the N available measured pairs. The optimized operator should satisfy two opposite conditions: (i) the best possible accuracy at reproducing the boundary drying curves used for operator optimization, and (ii) the least possible sensitivity with respect to excluding any one pair from the calibration dataset. We also apply the suggested modelling approach for derivation of the inverse operator model that predicts the boundary wetting curves from their associated measured boundary drying curves, with possibility of verification of the predictive reliability. The predictive performance of both operator models is mainly good, and their reliability can be permanently enhanced by updating them with new incoming measured data.

We study the Stokes problem for the incompressible fluid with mixed nonlinear boundary conditions of subdifferential type. The latter involve a unilateral boundary condition, the Navier slip condition, a nonmonotone version of the nonlinear Navier–Fujita slip condition, and the threshold slip and leak condition of frictional type. The weak form of the problem leads to a new class of variational–hemivariational inequalities on convex sets for the velocity field. Solution existence and the weak compactness of the solution set to the inequality problem are established based on the Schauder fixed point theorem.

Under the effects of internal factors and the external environment, some customer requirements can be extremely sensitive to change; these are known as sensitive requirements. These requirements drive the identification and design of the relevant engineering characteristics. This study defines such characteristics as agile engineering characteristics (AECs), which are crucial for redesigning products and prolonging their service life but attract limited research and practice attention. The research question of identifying the product AECs is answered in this study, and three key issues are solved in the proposed methodology. First, the contribution of product engineering characteristics to customer requirements is calculated using an orthogonal experimental design, and the optimal level combination of engineering characteristics to satisfy the customer requirements is determined through the analysis of variation. Subsequently, the relative importance of engineering characteristics is calculated based on data envelopment analysis. Next, an agility index is defined by integrating the customer satisfaction degree, the relative importance degree of engineering characteristics, and the variation of the level of engineering characteristics, to identify the AECs. Finally, based on the identification of the AECs of an electric vehicle air-conditioning heat pump scroll compressor, the results are analysed and compared to illustrate the feasibility and effectiveness of the proposed method.

We consider two important problems concerning the interaction between a cycloid surface and a screw dislocation. First, we examine the interaction between a traction-free and charge-free periodic cycloid wavy surface and a screw dislocation under anti-plane mechanical and in-plane electrical loading in a hexagonal piezoelectric solid. With the aid of conformal mapping and analytic continuation, we derive an elementary closed-form solution of the two-dimensional analytic vector function in the image plane characterizing the electroelastic field in the piezoelectric solid. The stresses, electric displacements, strains and electric fields in both the corresponding Cartesian and the curvilinear coordinate systems are determined. The image force acting on the piezoelectric screw dislocation is then obtained using the generalized Peach–Koehler formula. For a cusped cycloid surface, the resultant stress and electric displacement intensity factors at the cusp tips and crack extension force on the cusp tips are presented. Secondly, we use essentially the same approach to investigate the problem of the interaction of a screw dislocation with a traction-free and conducting cycloid surface in a hexagonal piezoelectric half-plane. A simple dislocation emission criterion is proposed.

Shock and boundary-layer interactions in transonic airfoils are investigated by means of wall-modeled large-eddy simulation. A distinctive flow model, organized and chaotic, occurs in this regime d...

The problem of disseminating continuous data flow from a given source node to all other network nodes is known as the dynamic broadcast problem, which is also a fundamental problem in multi-hop wireless networks (e.g., wireless ad hoc and sensor networks). Due to link unreliability and node mobility, the topology of a network typically changes with time. Little work has been conducted to address the dynamic broadcast problem in time-varying wireless multi-hop networks, especially under the popular Signal-to-Interference-plus-Noise-Ratio (SINR) interference model. In this paper, we study the dynamic broadcast problem in SINR-based time-varying directed acyclic multi-hop wireless networks formed by point-to-point wireless links. We consider the SINR-based link transmission rate model involved in the slot-based link scheduling. We first prove a tight upper bound for the broadcast capacity of the multi-hop wireless networks under study. We then propose an online max-weight Throughput-Optimal Dynamic Broadcast algorithm (TODB) which performs link weight allocation, link scheduling, and data forwarding for each time slot according to the current network connectivity and data reception rates of nodes. We derive the throughput-optimality of the TODB algorithm by proving that the broadcast throughput of TODB can achieve the aforementioned upper bound of the broadcast capacity. We evaluate the performance of TODB in terms of throughput and latency via simulations and the results validate its effectiveness.

This paper presents a hybrid method to assess the rail health with the focus on a specific type of rail surface defect called head check. The proposed method uses physics-based and data-driven models in order to model defect initiation and defect evolution on a rail for a given rail traffic tonnage. Ultrasonic (US) and Eddy Current (EC) defect detection measurements are used to provide Infrastructure Managers (IMs) with insight in the current rail condition. The defect initiation results obtained from the first part of the hybrid method which consists of the physics-based model is successfully validated with the EC measurements. Furthermore, the US and EC measurements are utilized to derive a data-driven model for defect evolution. Finally, a set of robust and predictive Key Performance Indicators (KPIs) are proposed to quantify the future condition of the rail based on different characteristics of rail health resulting from the defect initiation and defect evolution analysis.

Flow field distribution plays a vital role in electrochemical machining (ECM) because it can directly affect the machining stability and accuracy of ECM. In counter-rotating electrochemical machining (CRECM), the uniformity of the flow field is difficult to control due to the complicated and changeable flow channel shape. Through the simulation of the conventional lateral fluid flow pattern, it is found that the complexity of the flow channel with grid structures makes the flow field of machining area strongly disordered, which leads to the low velocity zones and dead zones. Based on the simulation results, a new electrolyte flow pattern with an auxiliary internal fluid is proposed, which can remarkably improve the uniformity of flow field by apply supplementary electrolyte to the machining area. Experimental results show that the new flow pattern effectively improves the machining stability of CRECM, and enhances the machining precision of grid structures, the sidewall taper angle is reduced from 29.3° to 7.7°.

A series of flight experiments have demonstrated a novel approach to measuring path-resolved optical turbulence quantities, such as Cn2, along an air-to-ground slant path. This paper describes the ...

This study addresses the experimental validation of a linear time-invariant (LTI) energy-maximizing control strategy for wave energy converters (WECs), applied to a 1/20 scale Wavestar WEC. To fulfill this objective, system identification routines are utilized to compute a mathematical (parametric) model of the input-output dynamics of the device, suitable for control design and implementation. With this parametric model, the so-called LiTe-Con energy-maximizing strategy, recently published in the literature, is designed, synthesized, and tested under irregular wave excitation in the wave basin at Aalborg University. Given that the LiTe-Con requires instantaneous knowledge of the wave excitation effects, estimates are provided by means of an unknown-input Kalman filter, designed in close synergy with the so-called internal model principle. For the experimental assessment, both controller and estimator are directly implemented in a real-time architecture. The performance of the LiTe-Con is evaluated in terms of energy-absorption, showing consistent results with respect to those obtained in numerical simulation, hence validating the LiTe-Con controller in a realistic real-time scenario.

This letter discusses the eco-driving problem, considering both electric and conventional powertrains, and presents a pathway to solving it numerically using an indirect collocation method. Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve. This letter introduces smooth approximations to convert the original problem to an unconstrained (and penalized) smooth boundary-value problem. This approach eliminates the discussion of the switching structure and leads to a lightweight Newton-method-based solution procedure.

Ignition overpressure (IOP) is a principal dynamic load experienced by a launch vehicle during liftoff. The IOP arises due to the sudden ignition of the solid rocket boosters (SRBs) of a launch veh...

This study has investigated the tensile deformation and fracture behavior of friction stir processed hypereutectic Al-Si-Cu alloy at ambient and high temperatures. The high-temperature tensile tests were performed at 300 °C, 400 °C, and 500 °C and a strain rate of 0.001−0.1 s−1. It was observed that for the as-cast alloy, as the strain rate increased at ambient temperature, the ultimate tensile stress decreased from 125.32 MPa to 20.34 MPa, while for the friction stir processed alloy under the same condition, the ultimate tensile stress reduced from 316.23 MPa to 215.91 MPa. Friction stir processing increased the ductility and mechanical properties of the alloy at high temperatures. At a constant strain rate of 0.1 s−1 and with temperature increment from 300 °C to 500 °C, the ultimate tensile strength decreased from 173.24 MPa to 22.57 MPa, resulting in the increased plasticity at the high temperature. As the strain rate incremented, the work hardening increased. Since dynamic recrystallization was easier at low strain rates, the fracture mechanism shifted from dislocation motion to grain boundary slip, which concentrated the deformation at the grain boundary and increased the plasticity. As the temperature grew and the strain rate declined, the stress-strain curve became serrated. The formation of serration in the stress-strain curve could be related to the dynamic strain aging and the occurrence of dynamic recrystallization.

A comprehensive benchmarking study has been carried out to determine the influence of the mesh formulation and chip separation methods on the reliability and accuracy of finite element modelling of large diameter drilling operations. The Coupled Eulerian–Lagrangian and the updated-Lagrangian (with element deletion) formulations available in ABAQUS/Explicit, together with the updated-Lagrangian (with re-meshing) formulation in DEFORM 3D are compared by simulating through-coolant drilling of AISI 1045. The Johnson–Cook damage model was implemented by a sub-routine in DEFORM 3D to ensure a consistent damage model is implemented across the formulations. Experimentally measured drilling thrust force, torque, and chip thickness values were used to compare the models performance and assess the accuracy of the predictions. The updated-Lagrangian with dynamic re-meshing was found to be the best performing methodology concerning the accuracy of predictions, whilst the Coupled Eulerian–Lagrangian methodology significantly under-predicted the drilling thrust force and torque. Due to numerical instabilities and computational cost, the updated-Lagrangian with element deletion method is not recommended to model large diameter drilling.

This paper presents an approach for the simulation of cutting processes with a dexel based-simulation considering process damping. The approach allows an independent modeling of engagement parameters for both rake and flank faces of arbitrary tool and workpiece geometries including dynamic behavior for the first time. A method is introduced for calculating the indentation volume of the flank face independently of the rake face. Therefore, the oriented sweep volume is introduced. The indentation volume of the flank face is used to model process damping for improving stability and dimensional form error prediction. For verification, experimental milling tests are carried out to create stability charts and surfaces. Both, the stability and surface prediction of the approach are analyzed for a chamfered tool, where a flank face - workpiece contact occurs, and an unchamfered tool, where no flank face - workpiece contact occurs. Even though the prediction accuracy of the stability limit can be improved compared to different approaches, there are significant differences between simulation and experiment. Thus, there is still a high need for a more accurate modelling of the process damping effect.

Friction stir welding and processing are widely used for joining of aluminum alloys and composites and fabrication of aluminum matrix composites. However, the friction stirred plates possess different microstructural zones which create significant difference in local properties and heat treatment is required to establish uniformity. In this article, the state-of-the-art of heat treatment on FSWed/FSPed aluminum alloys is discussed. The effects of heat treatment time and temperature on microstructural appearances and mechanical properties are examined thoroughly. Special attention is provided on the change in the state of precipitates by different heat treatment processes. Also, the effects of different heat treatment techniques are compared. Finally, some ideas regarding direction of new research related to current topic are addressed.

Having stepped into the era of information explosion, storing, processing and analyzing the vast data sometimes are quite intractable problems. However, it is impossible for personal computer or devices to tackle with such heavy workloads. Then, companies that provides cloud computational services come into business. Aiming at minimizing the expenditures, the most important part is how many cloud services the customers should reserve in advance because different amounts they consume will yield different expense. The emerging machine learning method provides a powerful tool to address such a prediction problem. In this paper, we propose a hierarchical Pythagorean fuzzy deep neural network to forecast the quantity of requisite cloud services. Besides the employment of fuzzy logic, the neural representation is also utilized as a complementary method. The knowledge acquired from fuzzy and neural perspectives are coalesced as the final transformed data to be put into the learning systems. Based on the anticipation of the deep neural network, the consumers are able to decide the amount of cloud services to purchase. Numerical results based on the real data set from Carnegie Mellon University demonstrate that the proposed model yields the economical predictions and outperforms the prediction by the traditional neural network.

In this paper, a functionally graded material column that is simply supported at one end and clamped at the other is considered. The buckling mode is postulated as a high-order polynomial. Six nove...

A finite element model (FEM) of the bracket arm of wrecker is developed and the mechanical behavior under six representative conditions is studied in this paper. Stress test experiment is carried out to validate the presented FEM. Comparison analyses show that results predicted from the FEM are in good agreement with those obtained from the test experiment. Moreover, the mechanical behavior analyses also give the danger working conditions for each component of the bracket arm. Based on the stress distributions under the danger working condition, structural improvement is conducted for the component which is prone to material failure. Mechanical behavior analyses of the improved structures are also carried out in this paper. Numerical analysis results show that the maximum stresses of each improved component of the bracket arm are all reduced to close or below the allowable stress. This indicted that the load bearing capacities of each component are improved effectively and meet the requirements of engineering applications.

The landing impact that occurs during aircraft touchdown results in the development of significant loads and accelerations within the airframe. Accurate knowledge of the landing loads is necessary ...

With the increasing demand for light weight design in industries such as aerospace and automotive, sheet metallic materials with high strength and low density have been intensively manufactured and widely applied. However, plastic deformation induced surface roughening is an undesirable and a practically unavoidable phenomenon for sheet metallic materials and becomes the subject of great attention in recent years. The evolution of surface roughening plays important roles in the strain limit of the deformation and also significantly influences the product quality and application. This paper provides a comprehensive overview of both experimental and numerical modelling contributions to understand the surface roughening behaviour of sheet metallic materials during various plastic deformation and manufacturing processes. It has been found that roughening of the free surface or necking of the interface is induced by grain scale strain heterogeneity and strongly dependent on the strain the material experienced, strain state and direction, grain size and texture, lubrication, mechanical properties of materials, rolling parameters, etc. By controlling and optimising these parameters, the surface roughening can be optimised for different materials and processing techniques to suit different applications.

The out-of-plane and in-plane deployment dynamics of a flexible space structure, namely, a solar sail quadrant consisting of a membrane attached to two support booms, are considered. The equations ...

A direct updating approach for stiffness and damping matrices based on eigenstructure assignment is presented. The approach (which preserves symmetry, connectivity, and constraints imposed by stati...

A proper orthogonal decomposition-based B-splines B\'ezier elements method (POD-BSBEM) is proposed as a non-intrusive reduced-order model for uncertainty propagation analysis for stochastic time-dependent problems. The method uses a two-step proper orthogonal decomposition (POD) technique to extract the reduced basis from a collection of high-fidelity solutions called snapshots. A third POD level is then applied on the data of the projection coefficients associated with the reduced basis to separate the time-dependent modes from the stochastic parametrized coefficients. These are approximated in the stochastic parameter space using B-splines basis functions defined in the corresponding B\'ezier element. The accuracy and the efficiency of the proposed method are assessed using benchmark steady-state and time-dependent problems and compared to the reduced order model-based artificial neural network (POD-ANN) and to the full-order model-based polynomial chaos expansion (Full-PCE). The POD-BSBEM is then applied to analyze the uncertainty propagation through a flood wave flow stemming from a hypothetical dam-break in a river with a complex bathymetry. The results confirm the ability of the POD-BSBEM to accurately predict the statistical moments of the output quantities of interest with a substantial speed-up for both offline and online stages compared to other techniques., Comment: 45 pages, 15 figures

To use effectively the shell in high-performance applications, analyzing the effect of hygrothermal effects on a piezoelectric delamination event is necessary. A laminated piezoelectric cylindrical shell with delamination is first established under hygrothermal effects, followed by an internal force analysis and an energy analysis of the shell. Then, a parametric vibration equation of the Mathieu for the shell is obtained by using the energy variation of the Rayleigh-Ritz method; later on, the harmonic balance method is employed to solve this equation. Finally, the effects of delamination parameters, geometric parameters, hygrothermal effects, and piezoelectric materials on the shell under uniformly distributed axial load are discussed.

Water-based suspensions with nanoparticles as additives have been developed to replace oil-based lubricants for green manufacturing. Optimisation of nanosuspension formulation can enhance their performance and thereby reduce manufacturing costs. Nevertheless, developing high-performance water-based nanosuspensions requires an in-depth understanding of the role of nanoadditives in lubrication. This review summarises the formulation of water-based nanosuspensions, their tribological properties, and lubrication mechanisms. Technical issues are systematically addressed concerning the applications of nanosuspensions in the rolling of steels, machining of difficult-to-cut metals, and abrasive shaping of hard-brittle ceramics. This review facilitates understanding water-based nanolubrication to enable formulating nanosuspensions with a satisfactory manufacturing performance. The review outcomes indicate that oxide-based nanosuspensions are suitable candidates for metal forming and machining processes due to their excellent anti-wear performance and high heat-carrying capacity. Carbon-based nanosuspensions are appropriate for ceramic shaping processes due to their excellent lubricity and superior resistance against abrasion. In particular, hybrid nanosuspensions consisting of at least two different types of nanoparticles demonstrate a superior synergistic performance in lubrication and cooling. They hence have great potential for future manufacturing processes for both ductile and brittle materials.

Since the seminal work of Daniele Mortari (“Moon-Sun Attitude Sensor,” Journal of Spacecraft and Rockets, Vol. 34, No. 3, 1997, pp. 360–364), the concept of an attitude sensor using images of illuminated celestial bodies has been pushed forward through the years. The basic idea consists of extracting two independent directions from the image of a celestial body, namely, the camera-to-planet and the planet-to-sun directions. The former is estimated from the center of an ellipse fitted to the imaged limb points and the latter from the symmetry axis of the illuminated region. These assumptions, however, only hold for far-distant spherical targets. In this work, the problem is reformulated in the framework of projective camera transformations of quadrics and conics, and an algorithm estimating the line of sight to the planet and the illumination direction from the limb and terminator ellipses, respectively, is presented. The method is applicable to any ellipsoidlike celestial body having known orientation. The algorithm is first validated on synthetically generated images and then tested using real pictures of Dione and Enceladus satellites gathered from Cassini spacecraft. Results show that the sensor concept returns rms errors in the order of the angular width of a pixel in computing the nadir direction, and subdegree accuracy in computing the sun direction.

In die-mold manufacturing and aircraft industry, many components that have thin-walled features are produced by turning operation. The major problem encountered during internal or external turning is cutting force induced deflection of workpiece along the periphery as well as axial length of a component. The present research work aims to develop a mathematical model for estimating dimensional and geometric errors during turning of thin-walled hollow cylinder qualitatively and quantitatively. In the proposed model, a mechanistic approach which is semi-analytical in nature is followed to achieve accuracy of the predicting results. First of all, process geometry model for thin-wall turning is developed based on process geometry variables such as uncut chip thickness, actual feed per revolution, actual depth of cut, peripheral cutting speed, effective cutting area etc. Using these process geometry variables and mechanistic cutting constants, a force model of turning is developed to estimate the tangential and radial force components. Later on, based on the predicted forces, tool-workpiece combined deflection model is developed to estimate radial, diametric and various geometric errors of the turned surface. The developed models are able to predict radial, diametric and various geometric errors such as straightness, circularly and cylindricity errors without conducting expensive actual machining operation. Hence, the present study will be helpful to take care of precautionary measures for controlling of dimensional and geometric errors more efficiently and reliably. Therefore, an attempt has been made to provide a basic platform to machining practitioners and process planners for in-depth comprehension and characterization of dimensional and geometric errors of the entire turned surface for varying machining conditions.

Recent researchers show that the shell structure and truss structure are emerging categories of light weight structure with unique mechanical properties and high customization potential, but they are difficult to manufacture by traditional methods. Inspired by the diving bell of water spider, the reticulated shell structure designed in this work combines the characteristics of the truss structure and the shell structure, and is fabricated by laser powder bed fusion (LPBF). The effect mechanism of strut angle on the manufacturability, compressive behaviors, energy absorption property, stress distribution, and fracture morphology were studied by experiment and simulation methods. The results showed that the relative densities of reticulated shell structures increased with the increase of strut angle, which was due to the existence of a large proportion of overhang structures in the reticulated shell structures. The compressive load-displacement curves of all reticulated shell structures showed a similar trend, including three stages, which were elasticity, subsidence, and densification. The reticulated shell structure with the strut angle of 75° had the highest specific energy absorption and energy absorption capacity. Finite element simulation results revealed that, with the change of the strut angle, the stress concentration in the reticulated shell structure significantly changed and directly affected the compression behavior of structures. The structure with the strut angle of 75° exhibited the lowest stress concentration level at key locations, leading to the best compressive behavior among structures.

Cohesive elements are commonly used to describe crack propagation in heterogeneous materials with toughening mechanisms. This work aims to provide a guideline on how these fracture parameters can be calibrated using notch opening displacements (NODs) measured via digital image correlation and force data from wedge splitting tests (WSTs). Weighted finite element model updating was applied to calibrate material and boundary condition parameters in the same framework. The influence of each parameter on force and NOD data are given together with uncertainties for the calibrated parameters. Numerical results were in very good agreement in terms of splitting force, NOD, displacement and gray level residual fields. It is shown that images obtained during WSTs focusing on the crack path (i.e., hiding the loading region) can be used to drive numerical simulations and obtain cohesive parameters.

This paper focuses on the configuration design of flexure hinges with a prescribed compliance matrix and preset rotational center position. A new method for the topology optimization of flexure hinges is proposed based on the adaptive spring model and stress constraint. The hinge optimization model is formulated by maximizing the bending displacement with a spring while optimizing the compliance matrix to a prescribed value. To avoid numerical instability, an artificial spring is used as an auxiliary calculation, and a new strategy is developed for adaptively adjusting the spring stiffness according to the prescribed compliance matrix. The maximum stress of flexure hinge is limited by using a normalized P-norm of the effective von Mises stress, and a position constraint of rotational center is proposed to predetermine the position of the rotational center. In addition, to reduce the error of the stress measurement, a simple but effective filtering method is presented to obtain a complete black-and-white design. Numerical examples are used to verify the proposed method. Topology results show that the obtained flexure hinges have the prescribed compliance matrix and preset rotational center position while also meeting the stress requirements.

Under ultra-reliable and low-latency communications (URLLC) for modern and future wireless networks, this work studies block-length-error probability (BLE) over an outdated-channel-state-information (oCSI) relay network deploying maximal ratio combining. Impact of finite-blocklength regimes on hybrid-automatic-repeat-request protocols with a finite pilot length is also studied. The network is operating under a generalised-Rician fading environment, which covers both line-of-sight (LoS) and non-LoS. The BLE is computed as a function of a bandwidth, payload, an oCSI coefficient, a diversity order and LoS power. Reliability-latency trade-off and effects of other parameters to URLLC performance are examined and discussed. Impact of system incoherence on URLLC performance will also be studied.

The continuous development of internal combustion engines has been permanently limited by pollutant emissions. Hence, in Europe, EURO pollution norms have been implemented, and constantly updated, becoming more restrictive in order to minimize pollution in the major urban areas. Water injection is one of the strategies being explored to improve engine efficiency. However, there is need to assess its influence on pollutant emissions. The paper aims to track the impact of water injection in reducing pollutant emissions. The present study was performed on a spark ignition side-valve engine with a water injection system in the intake manifold at constant load and engine speed, and various values for the ratio between water and fuel (W/F) ranging from 0.25 to 1.0 were tested. The tests were performed for two compression ratios of 7.8 and 11.7. CO, CO2, HC, and NOx emissions were tracked depending on the ignition advance. The maximum advance for each case is set by the knock limit.

Greater integration of materials, product and processes is demanded ultimately toward a knowledge-based control of advanced manufacturing. We propose a framework of high-performance manufacturing theory and methodology to enable the integrated design and processing of a product, with a material–product–process linking developed on the pivot role of surface integrity determining the final performance. Metal cutting, as a representative process of conventional manufacturing, is demonstrated for the new development of manufacturing from a trial-and-error approach to a knowledge-based approach under the framework. A physical model of integrated design and processing is established on thermodynamics for cutting of a metastable AISI 304 austenitic stainless steel component during processing under the multi-source constraints of component geometry, material and structure, where surface integrity changes in surface residual stress and martensitic phase fraction are predicted by FEM modeling. The profound processing effect is described by process signature that derives a quantitative correlation of processing loads in effective force/power input and material loading in transferred/dissipated thermal and mechanical energies to the surface integrity changes. A material-oriented regularization (MOR) method is thus contrived as incorporating the process signature by utilizing identified characteristic correlations of high sensitivity to solve the involved inverse problems. The processing parameters of cutting speed/depth of cut and the design parameters of geometry are synergistically determined through the required surface integrity toward a desired final fatigue performance. The high-performance manufacturing overcomes the intrinsic trial-and-error limitations of conventional manufacturing, knowledgeably considering the coupling effect of processing in the design otherwise merely employed as an empirical design criterion in the past.

Manufacturing high precision and high performance parts in aerospace, automotive and medical industries often requires machining of difficult-to-cut materials such as titanium, nickel and hardened alloyed steel alloys. Low productivity and environmental damage are major problems in cutting these materials, which vitally require optimized cooling strategies. High-pressure cutting fluid supply (HP CF) and cryogenic cooling lubrication (CRYO CL) are two of the most effective cooling lubrication approaches to increase tool life, productivity and avoid scrap production. The scientific and knowledge-based application of HP CF and CRYO CL had a pivotal role in improving the machining of difficult-to-cut materials, specifically in milling processes. In this context, the quantification of the cooling and lubrication effect of HP CF and CRYO CL is essential in order to adapt to the fluctuating heat generation at the cutting zone. The novel concept of a soft sensor for the quantification of the cooling and lubrication effect in the milling process is presented in this paper. This soft sensor integrates force measurements and transient temperature data from the process with the help of a mechanical model as well as an inverse temperature model. These models elevate the measured force and temperature signals to heat flows and power in the thermodynamic domain enabling an energy balancing in the real milling application. A telemetry system was used to measure the transient temperature in the milling tool with embedded thermocouples when milling 42CrMo4 and Ti-6Al-4 V in αβ and β conditions. This way the separated cooling versus lubrication effect of high-pressure cutting fluid supply and a single channel cryogenic cooling lubrication based on carbon dioxide (CO2) and oil is investigated and compared with dry machining at various cutting parameters and proceeding tool wear.

An explicit dynamic simulation of the vertical crash of a regional airliner’s middle fuselage section has been conducted to investigate its crashworthiness. The simulation result shows that there a...

An optimal real-time neural-network-based controller for an on-orbit service mission is proposed. The problem can be mathematically formulated as a complex optimal control problem due to the coupli...

We are seeing a growth in the number of connected vehicles in Vehicular Ad-hoc Networks (VANETs) to achieve the goal of Intelligent Transportation System (ITS). This is leading to a connected vehicular network scenario with vehicles continuously broadcasting data to other vehicles on the road and the roadside network infrastructure. The presence of a large number of communicating vehicles greatly increases the number and types of possible anomalies in the network. Existing works provide solutions addressing specific anomalies in the network only. However, since there can be a multitude of anomalies possible in the network, there is a need for better anomaly detection frameworks that can address this unprecedented scenario. In this paper, we propose an anomaly detection framework for VANETs based on deep neural networks (DNNs) using a sequence reconstruction and thresholding algorithm. In this framework, the DNN architectures are deployed on the roadside units (RSUs) which receive the broadcast vehicular data and run anomaly detection tasks to classify a particular message sequence as anomalous or genuine. Multiple DNN architectures are implemented in this experiment and their performance is compared using key evaluation metrics. Performance comparison of the proposed framework is also drawn against the prior work in this area. Our best performing deep learning-based scheme detects anomalous sequences with an accuracy of 98%, a great improvement over the set benchmark.

This paper explores the feasibility and benefits of a new way of the Phobos sample return delivery mission to a Phobos Sample Return (PSR) orbiter using the electrostatic field artificially generat...

A restraint protection system for front row occupant is designed according to the collision danger level. An algorithm based on driver response time margin is designed to determine the danger level of collision. The algorithm gives different possibility of collision, corresponding to different danger level, and corresponding starting different constraint protection device. The simulation model of automobile frontal collision was established in the dynamic simulation software MADYMO and verified by experiment. Compared with the traditional occupant restraint protection system, the simulation results show that the proposed active restraint protection system improves the protection effect of the occupant’s head and hip, while the damage evaluation indexes such as peak neck bending moment, chest acceleration and chest compression decrease obviously. Therefore, the designed active occupant restraint protection system can effectively reduce the degree of occupant injury.

Hybrid beamforming is a promising technique to reduce the complexity and cost of massive multiple-input multiple-output (MIMO) systems while providing high data rate. However, the hybrid precoder design is a challenging task requiring channel state information (CSI) feedback and solving a complex optimization problem. This paper proposes a novel RSSI-based unsupervised deep learning method to design the hybrid beamforming in massive MIMO systems. Furthermore, we propose i) a method to design the synchronization signal (SS) in initial access (IA); and ii) a method to design the codebook for the analog precoder. We also evaluate the system performance through a realistic channel model in various scenarios. We show that the proposed method not only greatly increases the spectral efficiency especially in frequency-division duplex (FDD) communication by using partial CSI feedback, but also has near-optimal sum-rate and outperforms other state-of-the-art full-CSI solutions., Submitted to IEEE Transactions on Wireless Communications

Water injection in internal combustion engines is mainly used for additional cooling of the combustion chamber and knock suppression. The main advantages of the water injection are the potential for the enhancement of the performance of the engine. Studies conducted so far have aimed to track engine performance at maximum load and fuel consumption (brake-specific fuel consumption BSFC). Specialized literature is less consistent as regards to the injection of water at medium and low loads. This work monitors the effects of water injection at medium loads and the evolution processes of the four-strokes in the engine with and without water injection. A side-valve, air cooled natural aspirated engine with water and fuel injections in the intake manifold was used for this study. The work during expansion was increased, but this trend was reversed by the higher loads required during intake, compression and exhaust strokes, leading to a reduction in the indicated efficiency when water was injected.

An electrospray thruster designed for nanosatellites is introduced in this paper. The thruster has a compact size featuring a passive propellant transport method through the use of porous materials...

Two types of aeroacoustic wind-tunnel test section configurations have been tested in the NASA Langley Quiet Flow Facility. The first is a more traditional open-jet configuration, where test sectio...

Heterogeneous cloud radio access network (H-CRAN) has been deemed as a promising architecture for the fifth generation wireless networks. In H-CRAN, small remote radio heads (SRRHs) are deployed underlaying the macro remote radio head (MRRH) to boost the spectral efficiency. H-CRANs with dense RRHs suffer from severe inter-cell interference due to the random deployment of dense SRRHs, which limits its performance. In this paper, we propose an Edge-Aware RRH-Cooperation (EARC) scheme to mitigate the impact of both the cross-tier and co-tier interference. We partition the users into two groups, Cell Edge Device (CED) and Non-cell Edge Device (NED). These two groups, CED and NED, are mapped into two association modes, dual-association and single-association mode, respectively. In single-association mode, the NED associates with the RRH that provides the maximum received signal. On the other hand, in the dual-association mode, the CED associates with the two strongest RRHs where the two RRHs may belong to the same or different tier(s). Using tools from stochastic geometry, we quantify the performance gains of the proposed EARC scheme in terms of outage probability and ergodic rate. To further show the efficacy of the proposed scheme, we compare it to four schemes developed in the literature.

Real-time detection and control of the isolator shock-train leading edge (STLE) is important to the performance of high-speed air-breathing engines, such as dual-mode scramjets. Typically, the STLE...