Computational Parametric Analysis of Cellular Solids with the Miura-Ori Metamaterial Geometry under Quasistatic Compressive Loads

Origami-based metamaterials have widespread application prospects in various industries including aerospace, automotive, flexible electronics, and civil engineering structures. Among the wide range of origami patterns, the fourfold tessellation known as Miura-ori is of particular attraction to engineers and designers. More specifically, researchers have proposed different 3D structures and metamaterials based on the geometric characteristics of this classic origami pattern. Herein, a computational modeling approach for the design and evaluation of 3D cellular solids with the Miura-ori metamaterial geometry which can be of zero or nonzero thicknesses is presented. To this end, first, a range of design alternatives generated based on a numerical parametric model is designed. Next, their mechanical properties and failure behavior under quasistatic axial compressive loads along three perpendicular directions are analyzed. Then, the effects of various geometric parameters on their energy absorption behavior under compression in the most appropriate direction are investigated. The findings of this study provide a basis for future experimental investigations and the potential application of such cellular solids for energy-absorbing purposes.     

On Space Efficient Two Dimensional Range Minimum Data Structures

The two dimensional range minimum query problem is to preprocess a static m by n matrix (two dimensional array) A of size N=m⋅n, such that subsequent queries, asking for the position of the minimum element in a rectangular range within A, can be answered efficiently. We study the trade-off between the space and query time of the problem. We show that every algorithm enabled to access A during the query and using a data structure of size O(N/c) bits requires Ω(c) query time, for any c where 1≤c≤N. This lower bound holds for arrays of any dimension. In particular, for the one dimensional version of the problem, the lower bound is tight up to a constant factor. In two dimensions, we complement the lower bound with an indexing data structure of size O(N/c) bits which can be preprocessed in O(N) time to support O(clog ² c) query time. For c=O(1), this is the first O(1) query time algorithm using a data structure of optimal size O(N) bits. For the case where queries can not probe A, we give a data structure of size O(N⋅min {m,log n}) bits with O(1) query time, assuming m≤n. This leaves a gap to the space lower bound of Ω(Nlog m) bits for this version of the problem.     

Sterilizing tissue-materials using pulsed power plasma

This paper investigates the potential of pulsed power to sterilize hard and soft tissues and its impact on their physico-mechanical properties. It hypothesizes that pulsed plasma can sterilize both vascular and avascular tissues and the transitive layers in between without deleterious effects on their functional characteristics. Cartilage/bone laminate was chosen as a model to demonstrate the concept, treated at low temperature, at atmospheric pressure, in short durations and in buffered environment using a purposed-built pulsed power unit. Input voltage and time of exposure were assigned as controlling parameters in a full factorial design of experiment to determine physical and mechanical alteration pre- and post-treatment. The results demonstrated that, discharges of 11 kV sterilized samples in 45 s, reducing intrinsic elastic modules from 1.4 ± 0.9 to 0.9 ± 0.6 MPa. There was a decrease of 14.1 % in stiffness and 27.8 % in elastic-strain energy for the top quartile. Mechanical impairment was directly proportional to input voltage (P value < 0.05). Bacterial inactivation was proportional to treatment time for input voltages above 32 V (P < 0.001; R _Sq  = 0.98). Thermal analysis revealed that helix-coil transition decelerated with exposure time and collagen fibrils were destabilized as denaturation enthalpy reduced by 200 μV. We concluded by presenting a safe operating threshold for pulsed power plasma as a feasible protocol for effective sterilization of connective tissues with varying level of loss in mechanical robustness which we argue to be acceptable in certain medical and tissue engineering application.     

Smart production systems: automating decision-making in manufacturing environment

Smart production systems (SPS) are manufacturing systems capable of autonomously diagnosing their health and autonomously designing continuous improvement projects, leading to the desired productivity improvement. The main component of SPS, developed in this paper, is the Programmable Manufacturing Advisor (PMA), which evaluates the system's health and calculates optimal steps for continuous improvement. The analytics of PMA are based on the theory of Production Systems Engineering (PSE); the numerics of PMA are based on PSE Toolbox, which implements the PSE methods. In this paper, the PMA-based SPS architecture with manager-in-the-loop is described, theoretical/analytical foundations of PMA are outlined, its software/hardware implementations are commented upon, and demonstrations of PMA-based SPS operation are provided using two production systems: automotive underbody assembly (large volume manufacturing) and hot-dip galvanisation plant (small manufacturing organisation).     

Prediction of the effectiveness of rolling dynamic compaction using artificial neural networks and cone penetration test data

Rolling Dynamic Compaction(RDC),which is a ground improvement technique involving non-circular modules drawn behind a tractor,has provided the construction industry with an improved ground compaction capability,especially with respect to a greater influence depth and a higher speed of compaction,resulting in increased productivity. However,to date,there is no reliable method to predict the effectiveness of RDC in a range of ground conditions. This paper presents a new and unique predictive tool developed by means of artificial neural networks(ANNs) that permits a priori prediction of density improvement resulting from a range of ground improvement projects that employed 4-sided RDC modules;commercially known as"impact rollers". The strong coefficient of correlation(i.e. R0.86) and the parametric behavior achieved in this study indicate that the model is successful in providing reliable predictions of the effectiveness of RDC in various ground conditions.     

A multi-agent architecture for control of AGV systems

Agent is an autonomous, computational entity that can be viewed as perceiving its environment and acting upon it. Agents are event-driven objects that can be integrated in automated manufacturing environments to control certain tasks. In this paper a set of agents (a multi-agent system) is introduced to control an automated manufacturing environment. The architecture includes functions at the manufacturing cell level, materials handling and transport level, and factory scheduling level. Communication between these agents is accomplished by using a relational database (blackboard system). The relational database also integrates the requirements of a manufacturing execution system within the multi-agent task structure, which is unique to this architecture. Manufacturing cell and scheduling agents have been previously described in the literature. Here we focus our attention on the functions of the agents of the transport system, which is composed of a set of AGVs.     

An accurate and power-efficient period-modulator-based interface for grounded capacitive sensors

A low-power and high-resolution capacitance-to-period converter (CPC) based on period modulation (PM) for subnanometer displacement measurement systems is proposed. The presented circuit employs the interface developed in a previous work, “a grounded capacitance-to-voltage converter (CVC) based on a zoom-in structure,” further improving its performance through a symmetrical design of the applied autocalibration technique. The scheme is based on the use of a relaxation oscillator. To minimize the error contributed by the CPC circuitry, different precision techniques such as chopping, autocalibration, and active shielding are applied. The proposed CPC is realized in a 0.18-μm complementary metal-oxide-semiconductor (CMOS) technology, occupies an area of 0.5 mm², and consumes 135 μA from a 2-V power supply. In order to achieve optimal performance and avoid overdesigning, a noise estimation of various parts of the CPC has been done. Accordingly, for a 10-pF sensor capacitance, the overall CPC demonstrates a capacitance resolution of 0.5 fF for a latency of 128 microseconds, corresponding to an effective number of bits (ENOB) of 12.5 bits and an energy efficiency of 6 pJ/step. The nonlinearity error has been evaluated as well, resulting in a less than 0.03% full-scale span (FSS).     

Behavioral modeling of clock feed-through and channel charge injection non-ideal effects in SIMULINK for switched-capacitor integrator

Sigma–Delta modulator ADCs used in signal processing applications usually, are implemented by switched-capacitor (SC) circuits and CMOS transmission gates due to its simplicity for implementation. Channel charge injection (CCI) and clock feed-through (CFT) are two major non-ideal effects existing in TG switches and SC integrators reducing modulator total SNR, its linearity and its total gain. This paper presents a precise model for SC integrator including CCI and CFT non-ideal effects in MATLAB SIMULINK environment which allows designers to perform time-domain behavioral simulations of switched-capacitor (SC) Sigma–Delta modulators. Evaluation and validation of extracted models were performed via behavioral and transistor-level simulations for modeled SC integrator, second and third order modulators using SIMULINK and Agilent ADS environments with a generic 0.18 μm CMOS technology. Non-idealities and nonlinearities effects are apparently observed by comparing the ideal modulator in behavioral analysis and actual modulator in circuit-level environment.     

Hydrogen production by catalytic near-critical water gasification and steam reforming of glucose

Near-critical water gasification (NCWG) and steam reforming (SR) were investigated for the production of hydrogen from a biomass model compound (glucose) using fixed bed tubular reactor. Ruthenium/carbon and nickel/yttria stabilized zirconia (YSZ) were utilized to enhance the reaction rates of the two processes for NCWG and SR, respectively. NCWG experiments were performed at 200 bar and 360–450 °C, while SR experiments were conducted at 500–800 °C and atmospheric pressure. Although in both cases complete carbon gasification is achieved, gas composition, hydrogen selectivity and overall energy efficiency show strong dependencies on the type of process itself and the associated operating conditions. It is shown that operating the reforming reaction of glucose at high pressures and low temperatures (NCWG) results in a significant amount of methane and trace amounts of carbon monoxide. In contrast, gasification of glucose at atmospheric pressures and high temperatures (SR) leads to a methane-free gas stream that contains few percents of carbon monoxide. Considering energy recovery and neglecting the heat losses, the maximum cold gas efficiency of the NCWG and SR reached 78% and 91%, respectively. The features of the two catalytic reaction processes are discussed in terms of the experiments and process simulations.