Packing Method Research Articles

Generation of irregular particle packing with prescribed statistical distribution, spatial arrangement, and volume fraction

A method for packing irregular particles with a prescribed volume fraction is proposed. Furthermore, the generated granular material adheres to the prescribed statistical distribution and satisfies the desired complex spatial arrangement. First, the irregular geometries of the realistic particles were obtained from the original particle images. Second, the Minkowski sum was used to check the overlap between irregular particles and place an irregular particle in contact with other particles. Third, the optimised advance front method (OAFM) generated irregular particle packing with the prescribed statistical distribution and volume fraction based on the Minkowski sum. Moreover, the signed distance function was introduced to pack the particles in accordance with the desired spatial arrangement. Finally, seven biaxial tests were performed using the UDEC software, which demonstrated the accuracy and potential usefulness of the proposed method. It can model granular material efficiently and reflect the mesostructural characteristics of complex granular materials. This method has a wide range of applications where discrete modelling of granular media is necessary. • A method for packing irregular particles with the prescribed volume fraction is proposed. • The generated granular material can respect the prescribed statistical distribution. • The generated granular material can satisfy the desired complex spatial arrangement. • The packing speed is fast, and the volume fraction is better than most packing methods.

Efficient nitrogen removal through coupling biochar with zero-valent iron by different packing modes in bioretention system

Three kinds of bioretention were designed to explore the effects of zero-valent iron (ZVI) and biochar on the nitrogen removal performance and to seek a more reasonable packing method in this study. The results showed that the effluent removal rates of nitrate, ammonium and total nitrogen were 53.30 ± 12.68%, 98.41 ± 0.38% and 64.03 ± 8.72% respectively in Bioretention-3 during the rainfall events, while the nitrate concentration decreased gradually with the increase of drying time. According to the batch experiment, it was found that zero-valent iron could release continuously and stably in Bioretention-3 and Bioretention-1 due to the interception effect of biochar on dissolved oxygen. In addition, biochar in soil layer could protect zero-valent iron from excessive oxidation while biochar in the substrate layer could release organic matter to promote heterotrophic denitrification. Microbial community analysis showed that the dominant phyla were Proteobacteria (20.92–40.81%) and Actinobacteriota (9.89–24.54%). The dominant nitrifying genera was Nitrospira while there were also aerobic denitrifying bacteria (Sphingomonas, Bradyrhizobium and Chryseolinea, etc.) in soil layer. In the substrate layer, there was more ferrous iron-mediated autotrophic denitrification process (Thiobacillus, Geobacter and Denitratisoma, etc.) in Bioretention-1 and Bioretention-3 while a larger proportion of Dissimilatory Nitrate Reduction to Ammonium process (DNRA) (Bacillus, Desulfovibrio and Pseudomonas, etc.) in Bioretention-2. In general, this study showed that biochar addition in soil coupled with mixing zero-valent iron and biochar as substrate layer was a more stable and efficient design through various aspects of evidence. It provides a new way for how to use zero-valent iron and biochar to improve nitrogen removal capacity in stormwater management.

Use of steel slag and LAS-based modifying admixture in obtaining highly eco-efficient precast concrete products

This paper presents a study on improving the eco-efficiency of no-slump concrete for precast elements using Basic Oxygen Furnace Slag (BOFS). Recycled BOFS powders and aggregates have been produced to obtain mixtures with better particle size distribution and improved packing density based on a particle packing method. A comprehensive experimental investigation was carried out on mixtures with different cement contents (5%, 10%, and 15% vol.) and compaction energy levels (6, 10, and 20 blows in a sand rammer). A modifying admixture based on Linear Alkyl Benzene Sodium Sulfonate (LAS) has also been evaluated as a workability and cohesiveness enhancer for steel slag concretes. In addition, concrete eco-efficiency was evaluated by measuring the binder intensity (bi) and waste consumption. The highest compaction energy provided packing densities ranging from 0.78 to 0.80, and BOFS aggregates led to better mechanical performances. The BOFS concrete containing 15% cement obtained the best strength (52.1 MPa) and bi value (7.0 kg/m³/MPa), with a waste consumption of 2356.57 kg/m³. The mixture with the lowest cement consumption (5% - 121.56 kg/m³) and the highest consumption of waste (2637.82 kg/m³) reached 16 MPa, delivering a bi of 7.6 kg/m³/MPa.

Planning Irregular Object Packing via Hierarchical Reinforcement Learning

Object packing by autonomous robots is an important challenge in warehouses and logistics industry. Most conventional data-driven packing planning approaches focus on regular cuboid packing, which are usually heuristic and limit the practical use in realistic applications with everyday objects. In this paper, we propose a deep hierarchical reinforcement learning approach to simultaneously plan packing sequence and placement for irregular object packing. Specifically, the top manager network infers packing sequence from six principal view heightmaps of all objects, and then the bottom worker network receives heightmaps of the next object to predict the placement position and orientation. The two networks are trained hierarchically in a self-supervised Q-Learning framework, where the rewards are provided by the packing results based on the top height, object volume and placement stability in the box. The framework repeats sequence and placement planning iteratively until all objects have been packed into the box or no space is remained for unpacked items. We compare our approach with existing robotic packing methods for irregular objects in a physics simulator. Experiments show that our approach can pack more objects with less time cost than the state-of-the-art packing methods of irregular objects. We also implement our packing plan with a robotic manipulator to show the generalization ability in the real world.

HeLayers: A Tile Tensors Framework for Large Neural Networks on Encrypted Data

Privacy-preserving solutions enable companies to offload confidential data to third-party services while fulfilling their government regulations. To accomplish this, they leverage various cryptographic techniques such as Homomorphic Encryption (HE), which allows performing computation on encrypted data. Most HE schemes work in a SIMD fashion, and the data packing method can dramatically affect the running time and memory costs. Finding a packing method that leads to an optimal performant implementation is a hard task. We present a simple and intuitive framework that abstracts the packing decision for the user. We explain its underlying data structures and optimizer, and propose a novel algorithm for performing 2D convolution operations. We used this framework to implement an inference operation over an encrypted HE-friendly AlexNet neural network with large inputs, which runs in around five minutes, several orders of magnitude faster than other state-of-the-art non-interactive HE solutions.

Energy-Efficient Trajectory Design of a Multi-IRS Assisted Portable Access Point

In this article, we propose a framework for energy efficient trajectory design of an unmanned aerial vehicle (UAV)-based portable access point (PAP) deployed to serve a set of ground nodes (GNs). In addition to the PAP and GNs, the system consists of a set of intelligent reflecting surfaces (IRSs) mounted on man-made structures to increase the number of bits transmitted per Joule of energy consumed measured as the global energy efficiency (GEE). The GEE trajectory for the PAP is designed by considering the UAV propulsion energy consumption and the Peukert effect of the PAP battery, which represents an accurate battery discharge profile as a non-linear function of the UAV power consumption profile. The GEE trajectory design problem is solved in two phases: in the first, a path for the PAP and feasible positions for the IRS modules are found using a multi-tier circle packing method, and the required IRS phase shift values are calculated using an alternate optimization method that considers the interdependence between the amplitude and phase responses of an IRS element; in the second phase, the PAP flying velocity and user scheduling are calculated using a novel multi-lap trajectory design algorithm. Numerical evaluations show that: neglecting the Peukert effect overestimates the available flight time of the PAP; after a certain threshold, increasing the battery size reduces the available flight time of the PAP; the presence of IRS modules improves the GEE of the system compared to other baseline scenarios; the multi-lap trajectory saves more energy compared to a single-lap trajectory developed using a combination of sequential convex programming and Dinkelbach algorithm.

Medindo densidade de empacotamento e demanda de água do cimento Portland e MCSs pelo método da energia de mistura

Abstract Wet packing methods evaluate the packing density of fine materials through the determination of the apparent density and voids content of pastes with different water to solids (w/s) ratios. Its goal is to estimate the minimum water demand to achieve the maximum solids concentration in the mixture, a parameter applied to the mix design of cementitious composites based on particle packing theories. Since most methods based on apparent density are time-consuming and require a high volume of materials, this paper aims to evaluate the mixing energy method as an alternative for the wet packing method and to adapt it to be used for SCMs (supplementary cementitious materials). With a reduced time and material to perform the test, results demonstrate a better precision of the mixing energy due to its discrete measurement. The ideal water flow and initial volume of materials to perform the test on cement and SCMs are discussed.

Multi-objective steel plate cutting optimization problem based on real number coding genetic algorithm

The rectangular packing problem is an NP-complete combinatorial optimization problem. This problem occurs widely in social production scenarios, with steel plate cutting being one example. The cutting scheme for the rectangular packing problem needs to be improved because, without the globally optimal solution, there are many unnecessary edges in the steel cutting process. Based on a practical roll-fed disc shearing steel plate optimization problem, this paper explores a generalized packing method for rectangles of special dimensions and abstractly condenses complex quantitative relationships to establish a multi-objective mixed-integer nonlinear programming model. An innovative algorithm design based on a genetic algorithm is established to plan the cutting scheme in a high-speed and efficient way. The outcome is a utilization rate of up to 92.73% for raw materials and a significant reduction in labor, providing a guide for practical production and processing tasks. The advantages and disadvantages of the model and algorithm are discussed, and it is concluded that this rectangular packing method has strong universality and generalization ability, allowing rectangular packing tasks with large data volumes to be completed within a short time.

A new “Stethoscope” autopsy incision in comparison to various conventional incisions along with suturing techniques and body packing methods for post autopsy reconstruction

Post autopsy reconstruction (PAR) plays a vital role in the external appearance of dead bodies while handing over to grieving family members. Autopsy surgeons should not only be restricted to autopsy findings/techniques but should also give importance to PAR. Autopsy incision includes various conventional incisions like I, Y, and Modified Y-shaped. The most commonly used incision is I -shaped in most of the autopsy because it is easy for quick suturing but it produces a poor cosmetic appearance because suturing produces visible suture over the front of the neck and chest of a corpse and improper suturing in the skin flaps leads to gapping causes leakage of body fluids at the suture site. More often that leads to avoidable, unnecessary emotional distress for grieving family members. That creates a negative image of forensic practice in society and sometimes with administrative complaints. The authors conducted an observation based study on the medicolegal autopsy that included ten cases that involved “Stethoscope” and various conventional incisions and explored suturing techniques and body packing methods. The study observed that the proposed “Stethoscope” incision was feasible, less time-consuming for suturing, had an excellent cosmetic effect, and was cost-effective. The suturing technique revealed that invisible sutures leads to good cosmetic outcomes but is more time-consuming and costly. The body packing method showed the excellent result of no leakage of body fluid from the suture site. The authors proposed a “Stethoscope” method of incision that can be practiced and adopted for a better cosmetic appearance and humanitarian aspect for grieving relatives. The body packing method renders the body non-hazardous to the public and attendants while handling and transporting. The authors highlight the importance and sensitization of autopsy surgeon/mortuary staff to restructure the corpse with the best cosmetic appearance for the Dignified Management of the Dead and Humanitarian Forensics.

A simple method for perfect packing of squares of sidelengths n^{-1/2-epsilon}

A simple method for perfect packing a square by squares of sidelengths 1, 2^{-t}, 3^{-t}, 4^{-t},ldots is presented for 1/2<tleq 17/32.

File Packing from the Malware Perspective: Techniques, Analysis Approaches, and Directions for Enhancements

With the growing sophistication of malware, the need to devise improved malware detection schemes is crucial. The packing of executable files, which is one of the most common techniques for code protection, has been repurposed for code obfuscation by malware authors as a means of evading malware detectors (mainly static analysis-based detectors). This paper provides statistics on the use of packers based on an extensive analysis of 24,000 PE files (both malicious and benign files) for the past 10 years, which allowed us to observe trends in packing use during that time and showed that packing is still widely used in malware. This paper then surveys 23 methods proposed in academic research for the detection and classification of packed portable executable (PE) files and highlights various trends in malware packing. The paper highlights the differences between the methods and their abilities to detect and identify various aspects of packing. A taxonomy is presented, classifying the methods as static, dynamic, and hybrid analysis-based methods. The paper also sheds light on the increasing role of machine learning methods in the development of modern packing detection methods. We analyzed and mapped the different packing methods and identified which of them can be countered by the detection methods surveyed in this paper.

Enhancement of Antioxidant Property of N-Carboxymethyl Chitosan and Its Application in Strawberry Preservation

Bio-enzymatic grafting phenolic acid to chitosan derivative is an efficient and environmentally friendly molecular synthesis technology. In the present study, N-carboxymethyl chitosan (CMCS) was grafted with gallic acid (GA) using recombinant bacterial laccase from Streptomyces coelicolor as a catalyst. GA and CMCS were successfully grafted as determined by measuring amino acid content, Fourier transform infrared (FTIR) spectroscopy and ultraviolet-visible (UV-Vis) spectroscopy. Then, the effect of GA-g-CMCS coating on the freshness of strawberries at 20 ± 2 °C was explored. The physiological and biochemical quality indicators of strawberries during storage were monitored. The 1.5% GA-g-CMCS coating helped to protect the antioxidant properties and nutrients of strawberries and extend the shelf life. Specifically, it reduced the weight loss of strawberries during preservation (originally 12.7%) to 8.4%, maintained titratable acidity content (TA) residuals above 60% and reduced decay rate from 36.7% to 8.9%. As a bioactive compound, GA-g-CMCS has the potential to become an emerging food packing method. These results provide a theoretical basis and reference method for the subsequent synthesis and application of CMCS derivatives.

A quasi-physical method for random packing of spherical particles

In this work, a quasi-physical method for the random packing of spherical particles based on the equivalent spring structure and the principle of force equilibrium is proposed. The model is inspired by a meshing method “Distmesh”. For the purpose of generating a feasible packing, the proposed model calculates the displacements of each particle based on physical principles and disregards forces that may not help with convergence, thus offering a natural and possibly fast route towards the final packing configuration. The packing densities predicted by the proposed method are in good agreement with those predicted by other methods and the experimental results. Finally, the topological properties of the packing of particles with log-normal size distributions, binary mixtures and ternary mixtures are evaluated by radical tessellation. The results show that the particle size differences and the proportions of each kind of particles have significant effect on the packing properties of the mixture. • Proposing a new quasi-physical model for the random packing of particles. • The model is inspired by a meshing method, which can more easily form force grids. • The model offers a natural and possibly fast route towards the final packing. • The particle size and volume ratio have significant effect on the packing properties.

Boriding kinetics and mechanical properties of X65Cr14 martensitic stainless steel by pack method

In this task, some mechanical properties and diffusion kinetics of boronized layers on X65Cr14 martensitic stainless steel were investigated. The boronization treatments were carried out at 1123, 1173, 1223 and 1323 K with 2, 4, 6 and 8 hours using the packing process. The boronized layers were characterized by optical microscopy, X-ray diffraction, and micro-Vickers hardness tester. The boronized layers produced on X65Cr14 martensitic stainless steel exhibited smooth and regular morphology. The thickness of the boronized layer ranged from 9.1 to 98.3 μm with different treatment time and temperature. XRD analysis revealed the existence of FeB, Fe2B, and CrB compounds. The surface hardness increased from 410 to 1750-2050 HV0.05 after the boronization treatment. The activation energy of the layer was 206.53 kJ/mol.

COVID 19 WASTE MANAGEMENT PRACTICES IN A TERTIARY CARE HOSPITAL

Introduction: The world has witnessed positive environment implications of nationwide lockdowns brought down upon by Covid 19 such as cleaner rivers and clearer skies, the same is not the case with respect to solid waste management. Objective:To study the Covid 19 waste management practices and precautions taken in a tertiary care hospital. Methodology:A retrospective study from 1st April 2020 to 31st March 2021 was conducted at NIMS, Hyderabad. Direct observational study was done to assess the existing facility, manpower, workflow and practices followed. Results:An average of 252 kgs biomedical waste was generated daily. All the biomedical waste including the waste generated in covid 19 areas, Rapid antigen testing centre, RTPCR lab were segregated in separate colour coded bags and were transferred to collection room, where it was stored in different rooms based on the colour, ready to be collected by GJ Multiclave for treatment and disposal. Adequate number colour coded waste bins and needle destroyers were provided to covid areas. Also, hypochlorite solution was issued in adequate quantity. No calibrated weighing machine was available onsite in covid areas nor any biomedical waste registers were maintained in Covid wards and ICUs. Yellow bins were filled beyond 3/4th level due to PPE kits leading to spillage, but frequent collection of waste was followed. Whereas other bins were not filled beyond 3/4th level to avoid spillage. There was 100% compliance in segregating infectious sharps from non-sharps. There was 100% compliance in segregating waste in Covid ICUs and 90% compliance in the Covid wards. Double packing method was followed. On-site measures like treating PPE with hypochlorite was practiced. Storage in the facility was never beyond 48 hours. A total of 19 workers were posted in three shifts for collecting waste. Adequate PPE kits were provided to all the workers in Covid units apart from the regular safety equipment. 20:10 day rule was followed where the workers worked for 20days followed by 10 days of quarantine. Training of staff was on periodic basis. Separate lifting trolleys for covid areas were earmarked and disinfection with hypochlorite was practiced. Workers posted underwent routine RAT once a month and a quarantine of 15 days was given to the tested positive workers. Conclusion:On an average 252 kgs of biomedical waste generated per day. 100% compliance was observed in segregating biomedical waste in Covid ICUs and 90 % compliance in the Covid wards. On site measures like treating PPE kits with hypochlorite solution was practiced. Covid waste was transported in closed containers. Stored waste was disposed within 48 hours of collecting from wards. Regular training of health workers posted in wards improved waste management.

Liquid flow distribution in trickle bed reactors containing trilobed extrusions packed using different techniques

The performance of the Trickle Bed Reactor (TBR) critically depends on the gas-liquid flow distribution in the reactor, which in turn depends on the catalyst shape, size, and structure. Extensive research has been carried out with spherical particles (catalyst),whereas industrially more complex-shaped particles (Cylindrical, Trilobe, and Quadrilobe) are used. Little work has been reported for the liquid distribution in packed beds employing these shapes.In this work, the liquid distribution was investigated in a cylindrical column of internal diameter 100 mm, containing particles of diameter 1.3 mm trilobed extrusions and length 1.8–8.8 mm. The influence of different loading methods - Central single source, solid cone, and hollow cone, gas and liquid flow rates, variation along the height of the column were studied. Air-water system was used. Pressure drop was measured with the help of a manometer and Maldistribution index (Mf) was calculated based on the variation of quantity of water collected at column outlet.It was observed that the Mf decreased with the increase in both the gas and liquid flow rate which was due to better spreading of the fluids with the increasing gas and liquid flow rate. The decrease in the Mf with the increasing gas and liquid flow rate indicates better distribution as reported in the literature 0 (best distribution) and 1 (worst distribution). Further, it was also noted that the pressure drop increased with the increasing gas and liquid flow rate. The hollow cone packing method shows the better distribution confirmed from the bulk voidage, Mf profiles, pressure drop variation, and flow profiles. A correlation has been proposed for the two-phase pressure drop for three packing methods.

DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device

Recently, there has been an explosive growth of mobile and embedded applications using convolutional neural networks (CNNs). To alleviate their excessive computational demands, developers have traditionally resorted to cloud offloading, inducing high infrastructure costs and a strong dependence on networking conditions. On the other end, the emergence of powerful SoCs is gradually enabling on-device execution. Nonetheless, low- and mid-tier platforms still struggle to run state-of-the-art CNNs sufficiently. In this article, we present DynO, a distributed inference framework that combines the best of both worlds to address several challenges, such as device heterogeneity, varying bandwidth, and multi-objective requirements. Key components that enable this are its novel CNN-specific data packing method, which exploits the variability of precision needs in different parts of the CNN when onloading computation, and its novel scheduler, which jointly tunes the partition point and transferred data precision at runtime to adapt inference to its execution environment. Quantitative evaluation shows that DynO outperforms the current state of the art, improving throughput by over an order of magnitude over device-only execution and up to 7.9× over competing CNN offloading systems, with up to 60× less data transferred.

MGPM Methods for Rectangular Single-Size Printed Circuit Board Orthogonal Packing Problems

Printed circuit board (PCB) orthogonal packing problems derive from the massive circuit board production process in the electronic industry. In the early stage, it mainly relied on human experiences to make decisions on how to make the most of each sheet while meeting customers’ orders. Up till now, researchers in enterprises and academic circles are still trying to explore effective mathematical models and feasible optimization methods. In most cases, what PCB companies generally face is the orthogonal layout decision, which considers positioning each rectangle PCB piece (PCB-P) on a rectangle sheet board (panel) in an ideal way so that each panel has the minimal remains with the most PCB-Ps. In this paper, multi-round gradual packing methods (MGPMs) are proposed based on the idea of combinatorial optimization and dynamic programming. MGPMs include the depth priority-based method (MGPM-DP) and breadth priority-based branch-and-prune method (MGPM-BC). The former has the advantage of finding better solutions, while the latter has the advantage of consuming short computational time. Through extensive computational tests on real data from a PCB production enterprise in China, both MGPM-DP and MGPM-BC have achieved noticeable and satisfactory results compared with the simplex method, dynamic programming method, and a widely used industrial software (Yuanbo) in China.

Precise mix-design of Ultra-High Performance Concrete (UHPC) based on physicochemical packing method: From the perspective of cement hydration

• A physicochemical packing method to optimize the design of UHPC is proposed. • A new equivalent particle size distribution of hydrated cement is calculated. • The macro characteristics of the newly developed UHPC is evaluated. • The hydration kinetics of the newly developed UHPC is evaluated. • The microstructure development of the newly developed UHPC is evaluated. It is widely accepted that Ultra-High Performance Concrete (UHPC) could be designed by the employment of Modified Andreasen and Andersen (MAA) particle packing model. However, the traditional MAA model only takes into account that dry particles reach the dense packing status under physical conditions, without considering the chemical hydration of wet cement particles. To solve this problem, this study adopts a physicochemical packing method to optimize the mix-design of UHPC through establishing a new equivalent particle size distribution of hydrated cement by applying a multilayer spherical shell model. Based on this, the mix proportion of UHPC is redesigned and the properties of the optimized UHPC are evaluated afterwards. The results show that the optimized mix-design leads to higher particle packing density of UHPC, thereby improving the durability on the premise of guaranteeing the workability and mechanical properties. Meanwhile, the optimized mix-design can also achieve denser micro structures of UHPC matrix, which provides a valuable reference to design UHPC more scientifically and reasonably.

A Branch-and-Repair Method for Three-Dimensional Bin Selection and Packing in E-Commerce

Selecting a Parcel Type Portfolio to Reduce Unused Space in Transportation Wrongly sized parcels lead to unused space and inefficient transportation. With continuously increasing e-commerce and last-mile delivery volumes, available parcel types at a warehouse can significantly impact unused space that is transported. In “A Branch-and-Repair Method for Three-Dimensional Bin Selection and Packing in E-Commerce,” Fontaine and Minner solve the trade-off between cost of unused space and cost of parcel variety through optimizing the portfolio of available parcel types. To solve large instances with millions of binary decision variables, the authors develop an exact decomposition method that allows for relaxing many binary variables, improves branch-and-check by repairing infeasible solutions, and shows how to avoid solving many subproblems. A case study using real data shows the efficiency of the proposed method and the impact of the portfolio on unused transportation space.