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Records Added in February 2020
Records added in February 2020
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95. LAPSE:2020.0171
Hydrothermal Liquefaction of Microalga Using Metal Oxide Catalyst
February 3, 2020 (v1)
Subject: Reaction Engineering
Keywords: biocrude, hydrothermal liquefaction, metal-oxide catalyst, microalgae
The yield and composition of the biocrude obtained by hydrothermal liquefaction (HTL) of Nannocloropsis gaditana using heterogeneous catalysts were evaluated. The catalysts were based on metal oxides (CaO, CeO2, La2O3, MnO2, and Al2O3). The reactions were performed in a batch autoclave reactor at 320 °C for 10 min with a 1:10 (wt/wt) microalga:water ratio. These catalysts increased the yield of the liquefaction phase (from 94.14 ± 0.30 wt% for La2O3 to 99.49 ± 0.11 wt% for MnO2) as compared with the thermal reaction (92.60 ± 1.20 wt%). Consequently, the biocrude yields also raised in the metal oxides catalysed HTL, showing values remarkably higher for the CaO (49.73 ± 0.9 wt%) in comparison to the HTL without catalyst (42.60 ± 0.70 wt%). The N and O content of the biocrude obtained from non-catalytic HTL were 6.11 ± 0.02 wt% and 10.50 ± 0.50 wt%, respectively. In this sense, the use of the metal oxides decreased the N content of the biocrude (4.62 ± 0.15−5.45 ± 0.11 wt%), although, the... [more]
96. LAPSE:2020.0170
Entropy Generation and Dual Solutions in Mixed Convection Stagnation Point Flow of Micropolar Ti6Al4V Nanoparticle along a Riga Surface
February 3, 2020 (v1)
Subject: Materials
Keywords: dual solution, entropy generation, micropolar fluid, Riga plate, thermal radiation, titanium alloy nanomaterial
Entropy generation and dual solutions are rarely studied in the literature. An analysis is attempted here. More exactly, the present paper looks at the impact of radiation of a micropolar fluid on mixed convective flow containing the titanium alloy Ti6Al4V nanoparticle along with a Riga plate. The study of dual-nature solution for the entropy generation along a Riga surface was not being explored in the literature; therefore, the current model focuses on the dual solutions of this complex nature model. Riga surface is identified as an actuator of electromagnetic in which electrodes are accumulated alternatively. This array produces the behavior of electromagnetic hydrodynamic in the flow field. The transmuted leading equations were worked out through the formula of 3-stage Lobatto IIIA. Influences of exercising enormous parameters on temperature distribution, velocity, and micro rotation fields are portrayed and argued. More than one solution is achieved in opposing flow, while in the... [more]
97. LAPSE:2020.0169
Fluorescence and Molecular Simulation Studies on the Interaction between Imidazolium-Based Ionic Liquids and Calf Thymus DNA
February 3, 2020 (v1)
Subject: Modelling and Simulations
Keywords: binding energy, COSMO-RS, DNA, docking, ionic liquids
This work presents a molecular level investigation on the nature and mode of binding between imidazolium-based ionic liquids (ILs) ([Cnbim]Br where n = 2, 4, 6) with calf thymus DNA. This investigation offers valuable insight into the mechanisms of interactions that can affect the structural features of DNA and possibly cause the alteration or inhibition of DNA function. To expedite analysis, the study resorted to using molecular docking and COnductor like Screening MOdel for Real Solvents (COSMO-RS) in conjunction with fluorescence spectroscopic data for confirmation and validation of computational results. Both the fluorescence and docking studies consistently revealed a weak interaction between the two molecules, which corresponded to the binding energy of a stable docking conformation in the range of −5.19 to −7.75 kcal mol−1. As predicted, the rod-like structure of imidazolium-based ILs prefers to bind to the double-helix DNA through a minor groove. Interestingly, the occurrence o... [more]
98. LAPSE:2020.0168
Investigation and Improvement of Scalable Oxygen Reducing Cathodes for Microbial Fuel Cells by Spray Coating
February 3, 2020 (v1)
Subject: Biosystems
Keywords: Co3O4, microbial fuel cell, MnO2, MoS2, municipal wastewater, oxygen reduction reaction, spray method, wastewater treatment
This contribution describes the effect of the quality of the catalyst coating of cathodes for wastewater treatment by microbial fuel cells (MFC). The increase in coating quality led to a strong increase in MFC performance in terms of peak power density and long-term stability. This more uniform coating was realized by an airbrush coating method for applying a self-developed polymeric solution containing different catalysts (MnO2, MoS2, Co3O4). In addition to the possible automation of the presented coating, this method did not require a calcination step. A cathode coated with catalysts, for instance, MnO2/MoS2 (weight ratio 2:1), by airbrush method reached a peak and long-term power density of 320 and 200−240 mW/m2, respectively, in a two-chamber MFC. The long-term performance was approximately three times higher than a cathode with the same catalyst system but coated with the former paintbrush method on a smaller cathode surface area. This extraordinary increase in MFC performance con... [more]
99. LAPSE:2020.0167
Understanding TiN Precipitation Behavior during Solidification of SWRH 92A Tire Cord Steel by Selected Thermodynamic Models
February 3, 2020 (v1)
Subject: Modelling and Simulations
Keywords: segregation models, solidification, TiN inclusion, tire cord steel
Tire cord steel is widely used in the tire production process of the vehicle manufacturing industry due to its excellent strength and toughness. Titanium nitride (TiN) inclusion, existing in tire rod, has a seriously detrimental effect on the fatigue and drawing performances of the tire steel. In order to control its amount and morphology, the precipitation behavior of TiN during solidification in SWRH 92A tire cord steel was analyzed by selected thermodynamic models. The calculated results showed that TiN cannot precipitate in the liquid phase region regardless of the selected models. However, the precipitation of TiN in the mushy zone would occur at the final stage during the solidification process (at solid fractions greater than 0.98) if the LRSM (Lever-rule model was applied for the N and Scheil model for Ti) or Ohnaka models (without considering the effect of carbon on secondary dendrite arm spacing (SDAS)) were adopted. For the Ohnaka model, in the case when the effect of carbon... [more]
100. LAPSE:2020.0166
Analysis of Dynamic Characteristics and Control Strategies of a Solvent Dehydration Distillation Column in a Purified Terephthalic Acid Plant
February 3, 2020 (v1)
Subject: Process Control
Keywords: control strategies, dynamic analysis, solvent dehydration column
In this study, a solvent dehydration column of purified terephthalic acid (PTA) plant was used as the research object. Based on a dynamic model of the solvent dehydration column, a dynamic sensitivity analysis of the key parameters was carried out using Aspen Dynamics. After the dynamic model reached stability, the reflux rate, methyl acetate concentration, and reflux temperature of the solvent dehydration column were adjusted and the changes of the key separation indexes under the corresponding disturbance were analyzed. According to the analysis results, a sensitive plate temperature controller was added to carry out the dynamic sensitivity analysis. In addition, the acetic acid (HAc) concentration of the bottom of the column was found to be unstable in the dynamic sensitivity analysis. Considering the HAc concentration controller of the column bottom, two control strategies were designed. By analyzing the dynamic response of the feed flow disturbance under different control strategi... [more]
101. LAPSE:2020.0165
Multimode Operating Performance Visualization and Nonoptimal Cause Identification
February 3, 2020 (v1)
Subject: Process Operations
Keywords: multi-space principal component analysis, multimode process, performance assessment, self-organizing map, subtractive clustering
In the traditional performance assessment method, different modes of data are classified mainly by expert knowledge. Thus, human interference is highly probable. The traditional method is also incapable of distinguishing transition data from steady-state data, which reduces the accuracy of the monitor model. To solve these problems, this paper proposes a method of multimode operating performance visualization and nonoptimal cause identification. First, multimode data identification is realized by subtractive clustering algorithm (SCA), which can reduce human influence and eliminate transition data. Then, the multi-space principal component analysis (MsPCA) is used to characterize the independent characteristics of different datasets, which enhances the robustness of the model with respect to the performance of independent variables. Furthermore, a self-organizing map (SOM) is used to train these characteristics and map them into a two-dimensional plane, by which the visualization of th... [more]
102. LAPSE:2020.0164
Correlation between Antibacterial Activity and Free-Radical Scavenging: In-Vitro Evaluation of Polar/Non-Polar Extracts from 25 Plants
February 3, 2020 (v1)
Subject: Biosystems
Keywords: antioxidant, natural product, oxidative stress, radical scavenging activity, wild edible plant
Objectives: The current study aimed to measure the antioxidant and antibacterial activities of 25 wild Palestinian edible plants, which were subjected to extraction by polar and non-polar solvents. Correlations between free radical scavenging activity and antibacterial activity of the extracts were assessed for both polar and non-polar fractions. Materials: Twenty-five wild edible plant species that are frequently consumed by people in Palestine (mainly in a rural area) were examined. Among them, 10 plant species were among those with the highest mean cultural importance values, according to an ethnobotanical survey that was conducted in the West Bank, Palestine, a few years ago. Method: The protocol of the DPPH assay for testing free-radical scavenging was utilized for determining EC50 values, while microdilution tests were conducted to determine the 50% inhibitory concentration (IC50) of the extracts for the microorganism Staphylococcus mutans. Results and Discussion: Eight extracts... [more]
103. LAPSE:2020.0163
A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets
February 3, 2020 (v1)
Subject: Planning & Scheduling
Keywords: chance-constrained programming, demand side management, microgrid, spot markets
Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market.
104. LAPSE:2020.0162
An Optimization Approach Considering User Utility for the PV-Storage Charging Station Planning Process
February 3, 2020 (v1)
Subject: Planning & Scheduling
Keywords: bi-level optimization, green energy, planning process, PV-storage charging stations, user utility
Based on the comprehensive utilization of energy storage, photovoltaic power generation, and intelligent charging piles, photovoltaic (PV)-storage charging stations can provide green energy for electric vehicles (EVs), which can significantly improve the green level of the transportation industry. However, there are many challenges in the PV-storage charging station planning process, making it theoretically and practically significant to study approaches to planning. This paper promotes a bi-level optimization planning approach for PV-storage charging stations. First, taking PV-storage charging stations and EV users as the upper- and lower-level problems, respectively, during the planning process, a bi-level optimization model for PV-storage charging stations considering user utility is established for capacity allocation and user behavior-based electricity pricing. Second, the model is converted into a single-level mixed-integer linear programming model using the piecewise linear util... [more]
105. LAPSE:2020.0161
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing
February 3, 2020 (v1)
Subject: Planning & Scheduling
Keywords: Genetic Algorithm, hot rolling, hot rolling planning, TOU electricity pricing
Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man−machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to bot... [more]
106. LAPSE:2020.0160
Integrated Forecasting Method for Wind Energy Management: A Case Study in China
February 3, 2020 (v1)
Subject: Planning & Scheduling
Keywords: combined model, data preprocessing technology, forecasting accuracy, multi-objective optimization algorithm, wind energy forecasting
Wind speed forecasting helps to increase the efficacy of wind farms and prompts the comparative superiority of wind energy in the global electricity system. Many wind speed forecasting theories have been widely applied to forecast wind speed, which is nonlinear, and unstable. Current forecasting strategies can be applied to various wind speed time series. However, some models neglect the prerequisite of data preprocessing and the objective of simultaneously optimizing accuracy and stability, which results in poor forecast. In this research, we developed a combined wind speed forecasting strategy that includes several components: data pretreatment, optimization, forecasting, and assessment. The developed system remedies some deficiencies in traditional single models and markedly enhances wind speed forecasting performance. To evaluate the performance of this combined strategy, 10-min wind speed sequences gathered from large wind farms in Shandong province in China were adopted as a case... [more]
107. LAPSE:2020.0159
Identification of Abnormal Processes with Spatial-Temporal Data Using Convolutional Neural Networks
February 3, 2020 (v1)
Subject: Process Monitoring
Keywords: convolutional neural network, pasting process, process image, spatial-temporal data
Identifying abnormal process operation with spatial-temporal data remains an important and challenging work in many practical situations. Although spatial-temporal data identification has been extensively studied in some domains, such as public health, geological condition, and environment pollution, the challenge associated with designing accurate and convenient recognition schemes is very rarely addressed in modern manufacturing processes. This paper proposes a general recognition framework for identifying abnormal process with spatial-temporal data by employing a convolutional neural network (CNN) model. Firstly, motivated by the pasting case study, the spatial-temporal data are transformed into process images for capturing spatial and temporal interrelationship. Then, the CNN recognition model is presented for identifying different types of these process images, leading to the identification of abnormal process with spatial-temporal data. The specific architecture parameters of CNN... [more]
108. LAPSE:2020.0158
A Modular Framework for the Modelling and Optimization of Advanced Chromatographic Processes
February 3, 2020 (v1)
Subject: Process Design
Keywords: CADET-Process, column configuration, Optimization, preparative chromatography, process design
A framework is introduced for the systematic development of preparative chromatographic processes. It is intended for the optimal design of conventional and advanced concepts that exploit strategies, such as recycling, side streams, bypasses, using single or multiple columns, and combinations thereof. The Python-based platform simplifies the implementation of new processes and design problems by decoupling design tasks into individual modules for modelling, simulation, assertion of cyclic stationarity, product fractionation, and optimization. Interfaces to external libraries provide flexibility regarding the choice of column model, solver, and optimizer. The current implementation, named CADET-Process, uses the software CADET for solving the model equations. The structure of the framework is discussed and its application for optimal design of existing and identification of new chromatographic operating concepts is demonstrated by case studies.
109. LAPSE:2020.0157
A Hybrid Framework for Simultaneous Process and Solvent Optimization of Continuous Anti-Solvent Crystallization with Distillation for Solvent Recycling
February 3, 2020 (v1)
Subject: Process Design
Keywords: crystallization, Distillation, PC-SAFT, process design, solvent design
Anti-solvent crystallization is frequently applied in pharmaceutical processes for the separation and purification of intermediate compounds and active ingredients. The selection of optimal solvent types is important to improve the economic performance and sustainability of the process, but is challenged by the discrete nature and large number of possible solvent combinations and the inherent relations between solvent selection and optimal process design. A computational framework is presented for the simultaneous solvent selection and optimization for a continuous process involving crystallization and distillation for recycling of the anti-solvent. The method is based on the perturbed-chain statistical associated fluid theory (PC-SAFT) equation of state to predict relevant thermodynamic properties of mixtures within the process. Alternative process configurations were represented by a superstructure. Due to the high nonlinearity of the thermodynamic models and rigorous models for dist... [more]
110. LAPSE:2020.0156
Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing
February 3, 2020 (v1)
Subject: Process Design
Keywords: antibodies, biologics manufacturing, PAT, precipitation, process modeling, QbD
The demand on biologics has been constantly rising over the past decades and has become crucial in modern medicine. Promising approaches to cope with widespread diseases like cancer and diabetes are gene therapy, plasmid DNA, virus-like particles, and exosomes. Due to progress that has been made in upstream processing (USP), difficulties arise in downstream processing and demand for innovative solutions. This work focuses on the integration of precipitation using a quality by design (QbD) approach for process development. Selective precipitation is achieved with PEG 4000 resulting in an HCP depletion of ≥80% respectively to IgG. Dissolution was executed with a sodium phosphate buffer (pH = 5/50 mM) reaching an IgG recovery of ≥95%. However, the central challenge in process development is still an optimal process design, which is transferable for a broad molecular variety of new products. This is where rigorous modeling becomes vital in order to generate digital twins to support early-s... [more]
111. LAPSE:2020.0155
Supporting Design Optimization of Tunnel Boring Machines-Excavated Coal Mine Roadways: A Case Study in Zhangji, China
February 3, 2020 (v1)
Subject: Process Design
Keywords: constitutive model, failure criterion, in-situ monitoring, numerical simulation, roadway supporting, tunnel boring machine
Tunnel Boring Machines (TBMs) are a cutting-edge excavating equipment, but are barely applied in underground coal mines. For TBM excavation projects involving the Zhangji coal mine, the surrounding rock properties, stress field, cross section geometry, as well as the excavation-induced stress path of TBM-excavated coal mine roadways are different from those of traditional tunnels or roadways. Consequently, traditional roadway supporting technologies and experiences cannot be relied on for this project. In order to research an appropriate supporting pattern for a TBM-excavated coal mine roadway, first of all, the constitutive model of roadway surrounding rocks was derived, and a rock failure criterion was proposed based on rock mechanical tests. Secondly, a three-dimension finite element model was established and computer simulations under three different supporting patterns were conducted. Stress redistribution, roadway convergence, and excavation damage zone ranges of surrounding rock... [more]
112. LAPSE:2020.0154
Numerical Comparison of a Combined Hydrothermal Carbonization and Anaerobic Digestion System with Direct Combustion of Biomass for Power Production
February 3, 2020 (v1)
Subject: Modelling and Simulations
Keywords: anaerobic digestion, bioenergy, direct combustion, Engineering Equation Solver, hydrothermal carbonization, power cycles
Two of the methods for converting biomass to fuel are hydrothermal carbonization (HTC) and anaerobic digestion (AD). This study is aimed at designing and analyzing two scenarios for bioenergy production from undervalued biomass (sawdust). In one of the scenarios (direct combustion or DC), raw biomass is burned in a combustor to provide the heat that is required by the Rankine cycle to generate electricity. In the other scenario (HTC-AD), the raw biomass first undergoes HTC treatment. While the solid product (hydrochar) is used to produce power by a Rankine cycle, the liquid by-product undergoes an AD process. This results in fuel gas production and it can be used in a Brayton cycle to generate more power. Energy and mass balance analysis of both scenarios were developed for each unit process by using Engineering Equation Solver (EES). The required data were obtained experimentally or from the literature. The performances of the proposed systems were evaluated, and a sensitivity analysi... [more]
113. LAPSE:2020.0153
Optimal Design of Standalone Photovoltaic System Based on Multi-Objective Particle Swarm Optimization: A Case Study of Malaysia
February 3, 2020 (v1)
Subject: Process Design
Keywords: levelized cost of energy (LCE), life cycle cost (LCC), loss of load probability (LLP), multi-objective optimization, Particle Swarm Optimization, standalone PV system
This paper presents a multi-objective particle swarm optimization (MOPSO) method for optimal sizing of the standalone photovoltaic (SAPV) systems. Loss of load probability (LLP) analysis is considered to determine the technical evaluation of the system. Life cycle cost (LCC) and levelized cost of energy (LCE) are treated as the economic criteria. The two variants of the proposed PSO method, referred to as adaptive weights PSO ( A W P S O c f ) and sigmoid function PSO ( S F P S O c f ) , are implemented using MATLAB software to the optimize the number of PV modules in (series and parallel) and number of the storage battery. The case study of the proposed SAPV system is executed using the hourly meteorological data and typical load demand for one year in a rural area in Malaysia. The performance outcomes of the proposed A W / S F P S O c f methods give various configurations at desired levels of LLP values and the corresponding minimum cost. The perform... [more]
114. LAPSE:2020.0152
Optimisation of the Autothermal NH3 Production Process for Power-to-Ammonia
February 3, 2020 (v1)
Subject: Process Design
Keywords: autothermal reactor systems, flexibility analysis, Haber–Bosch synthesis
The power-to-ammonia process requires flexible operation due to intermittent renewable energy supply. In this work, we analyse three-bed autothermal reactor systems for design and off-design performance for power-to-ammonia application. The five reactor systems differ in terms of inter-stage cooling methods, i.e., direct cooling by quenching (2Q), combination of indirect and direct cooling (HQ and QH) and indirect cooling (2H) with variations. At optimum nominal operation conditions, the inter-stage indirect cooling (2H) reactor systems result in the highest NH3 production. For off-design performance analysis, NH3 production is minimised or maximised by varying one of the following process variables at a time: inert gas, feed flow rate or H2-to-N2 ratio. For each variation, the effect on H2 intake, recycle stream load and recycle-to-feed ratio is also analysed. Among the three process variables, the H2-to-N2 ratio provided ca. 70% lower NH3 production and 70% lower H2 intake than at no... [more]
115. LAPSE:2020.0151
Design, Optimization, and Evaluation of Additively Manufactured Vintiles Cellular Structure for Acetabular Cup Implant
February 3, 2020 (v1)
Subject: Biosystems
Keywords: acetabular cup, additive manufacturing, cellular implant, cellular structure, design and optimization, finite element analysis, mechanical property
Cellular materials with very highly regulated micro-architectures are promising applicant materials for orthopedic medical uses while requiring implants or substituting for bone due to their ability to promote increased cell proliferation and osseointegration. This study focuses on the design of an acetabular cup (AC) cellular implant which was built using a vintiles cellular structure with an internal porosity of 56−87.9% and internal pore dimensions in the range of 600−1200 μm. The AC implant was then optimized for improving mechanical performance to reduce stress shielding by adjusting the porosity to produce stiffness (elastic modulus) to match with the bone, and allowing for bone cell ingrowth. The optimized and non-optimized AC cellular implant was fabricated using the SLM additive manufacturing process. Simulation (finite element analysis, FEA) was carried out and all cellular implants are finally tested under static loading conditions. The result showed that on the finite eleme... [more]
116. LAPSE:2020.0150
Assessment of Existing Photovoltaic System with Cooling and Cleaning System: Case Study at Al-Khobar City
February 3, 2020 (v1)
Subject: Energy Management
Keywords: cleaning, cooling, efficiency, photovoltaic systems, real case study, Renewable and Sustainable Energy
There is no denial that renewable energy is considered to be the most cost-competitive source of clean power in many parts of the world. Saudi Arabia’s vision 2030 aims at achieving the best by using different sources of renewable energy such as solar energy, wind energy, and others. The use of solar energy in particular for power generation will decrease the dependency on oil, and thus, decrease the greenhouse gasses. Solar panels efficiency tends to decrease with the accumulation of dust on their surface. Thus, a cleaning process requires assigning and employing labor, which increases the cost of running as well as high cost of machinery. The current study focuses on assessing and designing a simple auto self-cleaning system in order to improve the efficiency of the solar panel. The results showed that for the Al-Khobar region, Eastern Province, Kingdom of Saudi Arabia, the efficiency of the solar panels after cleaning was increased from 6% to an average of 12% at nominal temperature... [more]
117. LAPSE:2020.0149
A Hybrid Data-Based and Model-Based Approach to Process Monitoring and Control in Sheet Metal Forming
February 3, 2020 (v1)
Subject: Process Operations
Keywords: in-line measurement data, Industry 4.0, modelling and simulation, process monitoring and control, process performance, product quality, sheet metal forming
The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line... [more]
118. LAPSE:2020.0148
Static Deformation-Compensation Method Based on Inclination-Sensor Feedback for Large-Scale Manipulators with Hydraulic Actuation
February 3, 2020 (v1)
Subject: Process Control
Keywords: concrete pump, endpoint deviation, inclination sensor, large-scale manipulator, static deformation
Modern large-scale manipulators with hydraulic actuation like mobile concrete pump manipulators are increasingly used in industrial, construction, and other fields. Due to the large span of these manipulators, the static deformation accumulation to the endpoint has seriously affected the precise control of the endpoint. In this paper, we propose a static deformation-compensation method based on inclination sensor feedback for large-scale manipulators to reduce the deviation of the endpoint. Compared with the finite element method, this method does not need to consider many boundary conditions that are uncertain for flexible manipulators in most situations. It has appropriate accuracy and is universal for large-scale manipulators of different sizes and working under different loads. Based on a 24m-3R mobile concrete pump manipulator, the parametric simulation is carried out. The reliability of the static deformation-compensation method is verified, and the error is analyzed. The validit... [more]
119. LAPSE:2020.0147
Modeling of Parallel Movement for Deep-Lane Unit Load Autonomous Shuttle and Stacker Crane Warehousing Systems
February 3, 2020 (v1)
Subject: Planning & Scheduling
Keywords: autonomous shuttle and stacker crane warehousing system, compact storage systems, elitist non-dominated sorting genetic algorithm, warehouse operation process
The autonomous shuttle and stacker crane (AC/SC) warehousing system, as a new automated deep-lane unit load storage/retrieval system, has been becoming more popular, especially for batch order fulfilment because of its high flexibility, low operational cost and improved storage capacity. This system consists of a shuttle sub-system that controls motion along the x-axis and a stacker crane sub-system that controls motion along the y-axis and z-axis. The combination of shuttles and a stacker crane performs storage and retrieval tasks. Modelling the parallel motion is an important design tool that can be used to calculate the optimal number of shuttles for a given configuration of the warehousing system. In this study, shuttle movements from one lane to another are inserted into the stock-keeping unit (SKU) task queue, and convert such that they are consistent with the retrieval tasks. The tasks are then grouped according to their starting lane, and converted to an assembly-line parallel... [more]

