Transport Package Research Articles

Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty

Abstract This study proposes a theoretical model and assessment method for the resilience of High Consequence System (HCS), addressing the risk assessment and decision-making needs in critical system engineering activities. By analyzing various resilience theories in different domains and considering the characteristics of risk decision-making for HCS, a comprehensive theoretical model for the resilience of HCS is developed. This model considers the operational capability under normal environment (consisting of reliability and maintainability) and the safety capability under abnormal environment (consisting of resistance and emergence response ability). A case study is conducted on a spent fuel transportation packaging system, where the sealing performance after sealing ring aging is regarded as the reliability of the system and calculated using reliability methods, and impact resistance after impact is regard as resistance the impact safety of the packaging system is assessed using finite element analysis and surrogate modelling methods. The surrogate model fits the deformation output results of finite elements. Maintainability and emergency response ability are also essential elements of the resilience model for HCS facing exceptional events. The resilience variation of the spent fuel transportation packaging system is computed under the uncertainty of yielding stress of buffer material. The resilience of the packaging system is evaluated for different buffer thicknesses. The system's resilience decreases with higher uncertainty in the yielding stress of the buffer material, while it increases with thicker buffer materials. The improvement of emergency rescue ability will also lead to the improvement of system resilience.

Thermal insulation box design for maintaining cool temperature and the postharvest quality of okra

Postharvest loss of okra is caused by its high respiration rate and temperature fluctuations in the supply chain. To address this, five thermal insulation boxes were designed, combining different materials, and evaluated for okra quality during simulated transportation and storage. The treatments included the standard foam box, metalized foam sheet (two layers consisting of aluminum foil and expanded polyethylene), prototype-A (three layers consisting of dual layer of aluminum foil and expanded polyethylene), prototype-B (four layers consisting of aluminum foil, nonwoven, expanded polyethylene, and aluminum foil), and standard regular slotted container. Material tests revealed that aluminum foil and expanded polyethylene had the lowest thermal heat energy. The composite sandwich box design, prototype-A, demonstrated the highest maximum insulation time of 28 h and thermal resistance of 0.332 m2°C/W. Prototype-A and prototype-B effectively maintained low temperature fluctuation, minimized air and okra temperature changes, and maintained 6.19 to 8.25 % CO2, which was within an acceptable range of 4–10 % for okra. Both prototypes exhibited reduced percentage mass loss in okra below 5 %. Importantly, both prototypes demonstrated the lowest incidence of okra pod surface browning and maintained the quality for 6 d, surpassing metalized foam sheet and standard regular slotted container. These findings offer sandwich design with 3 or 4 layers as promising alternatives for thermal insulation boxes in cold chain management, enhancing the transport packaging of okra under ambient environments compared to the standard foam box.

High-throughput thermoelectric materials screening by deep convolutional neural network with fused orbital field matrix and composition descriptors

Thermoelectric materials harvest waste heat and convert it into reusable electricity. Thermoelectrics are also widely used in inverse ways such as refrigerators and cooling electronics. However, most popular and known thermoelectric materials to date were proposed and found by intuition, mostly through experiments. Unfortunately, it is extremely time and resource consuming to synthesize and measure the thermoelectric properties through trial-and-error experiments. Here, we develop a convolutional neural network (CNN) classification model that utilizes the fused orbital field matrix and composition descriptors to screen a large pool of materials to discover new thermoelectric candidates with power factor higher than 10 μW/cm K2. The model used our own data generated by high-throughput density functional theory calculations coupled with ab initio scattering and transport package to obtain electronic transport properties without assuming constant relaxation time of electrons, which ensures more reliable electronic transport properties calculations than previous studies. The classification model was also compared to some traditional machine learning algorithms such as gradient boosting and random forest. We deployed the classification model on 3465 cubic dynamically stable structures with non-zero bandgap screened from Open Quantum Materials Database. We identified many high-performance thermoelectric materials with ZT > 1 or close to 1 across a wide temperature range from 300 to 700 K and for both n- and p-type doping with different doping concentrations. Moreover, our feature importance and maximal information coefficient analysis demonstrates two previously unreported material descriptors, namely, mean melting temperature and low average deviation of electronegativity, that are strongly correlated with power factor and thus provide a new route for quickly screening potential thermoelectrics with high success rate. Our deep CNN model with fused orbital field matrix and composition descriptors is very promising for screening high power factor thermoelectrics from large-scale hypothetical structures.

SAFETY JUSTIFICATION FOR TRANSPORTATION OF NUCLEAR MATERIALS

The Institute of Atomic Energy of the National Nuclear Center of the Republic of Kazakhstan conducts a large number of studies to justify the safety of designed reactors and already operating reactors. Experiments are carried out both at in-pile and out-of-pile research installations. To implement these studies, there is a need to transport nuclear materials to the place where they are performed. Thus, it is necessary to justify the safety of nuclear material transportation. This paper presents neutronic calculations of the effective neutron multiplication factor to justify the safety of nuclear material transportation in accordance with the legislation of the Republic of Kazakhstan. The calculations used the most commonly transported type of nuclear materials – uranium dioxide (UO2) fuel pellets of various enrichments. Transportation was conducted using a transport packaging set IP-1, in accordance with the rules for the transportation of nuclear materials. Both normal and emergency conditions for the transportation of nuclear materials were modeled, taking into account the possibility of water leaking into the packaging and water getting into canisters with uranium dioxide fuel pellets. To determine the effective neutron multiplication factor (keff) of the transport and packaging set, the Monte Carlo calculation method was used in the MCNP5 program, with the ENDF/B-VII nuclear data library.

Color and Firmness Quality Changes of Java Apple During Postharvest Transportation and Storage

Transportation vibration adversely affects fresh produce during transportation. In addition, storage temperature affects the quality of fresh commodities. The physical changes in Java apples during transportation and storage were evaluated in this study. Java apples were transported from local farms to wholesale markets (180 km). Java apples were stored at room temperature (28°C) for six days. Physical qualities such as weight loss and firmness of the Java apple samples were evaluated. The RGB image acquisition system was used to assess changes in the color of the Java apple. The vibration showed that more than 70% of the acceleration occurred between 220-290 cm/s2 in the vertical and horizontal directions during transportation. Analysis showed that physical qualities, such as weight loss and firmness, were strongly affected by the packaging used, vibration during transportation, and storage temperature. The weight loss and reduction in firmness was highest in Java apples transported using wholesaler packaging (packaging A). The lightness, yellowness, and hue values decreased significantly because transportation vibration was relatively high, and the Java apples were stored at room temperature. Redness, total color difference, and color index increased significantly in Java apples that were transported using package A and stored at room temperature. The results showed that the use of transportation packaging affected changes in the physical quality of Java apples. Packaging A generally increase in weight loss, hardness, and changes in fruit color than other packaging types.

Natural Polysaccharide Film-Based Triboelectric Sensor for Fruit Transportation Collision Monitoring.

Transportation-induced damage to fresh produce is a big challenge in logistics. Current acceleration and pressure sensors for collision monitoring face issues of power dependency, high cost, and environmental concerns. Here, a self-powered and environmentally friendly triboelectric sensor has been developed to monitor fruit collisions in transportation packaging. Microcrystalline cellulose/chitosan and sodium alginate films were prepared as positive and negative tribo-layers to assemble a natural polysaccharide film-based triboelectric nanogenerator (NP-TENG). The NP-TENG's electrical output was proportional to the structure parameters (contact surface roughness and separation gap of the tribo-layers) and the vibration factors (force and frequency) and exhibited excellent stability and durability (over 100,000 cycles under 13 N at 10 Hz). The high mechanical-to-electrical conversion efficiency (instantaneous areal power density of 9.6 mW/m2) and force sensitivity (2.2 V/N) enabled the NP-TENG to be a potential sensor for monitoring fresh produce collisions in packaging during logistics. Transportation simulation measurements of kiwifruits verified that the sensor's electrical outputs increased with the vibration frequency and stacking layer while varying at different packaging locations. This study suggests that the NP-TENG can effectively monitor collision damage during fruit transportation, providing new insights into developing intelligent food packaging systems to reduce postharvest supply chain losses.

Optimal Design of Thermal Insulation Performance of Transport Packaging Box Based On Response Surface Algorithm

Optimal Design of Thermal Insulation Performance of Transport Packaging Box Based On Response Surface Algorithm

Graphene and its composites: A review of recent advances and applications in logistics transportation

AbstractThe research boom regarding graphene and its composites since its great discovery has continued to mount. Due to its superior electrical and thermal conductivities, high mechanical strength and lightweight characteristics, it has become a hugely potential candidate in hydrogen storage, aerospace, high‐performance composite, sensors, new energy batteries, etc. Here we provide a review of the application of graphene composites and extend into the field of transportation packaging to explore the possibilities of their application. The preparation process, mechanical properties and research methods of graphene structure are introduced, and the practical application of graphene‐reinforced composites is listed. The application prospects of graphene composites in packaging and transportation are presented.

The fastVFP code for solution of the Vlasov–Fokker–Planck equation

We describe the fastVFP code for solution of the Vlasov–Fokker–Planck equation for non-local electron transport and the generation of magnetic field, especially for application to laser-produced plasmas. We describe the essential features of the code that make it fast and robust and suitable for inclusion as a transport package in a fluid simulation. We present a few sample results that demonstrate the abilities of the code.

The MatHub‐3d first‐principles repository and the applications on thermoelectrics

AbstractFollowing the Materials Genome Initiative project, materials research has embarked a new research paradigm centered around material repositories, significantly accelerating the discovery of novel materials, such as thermoelectrics. Thermoelectric materials, capable of directly converting heat into electricity, are garnering increasing attention in applications like waste heat recovery and refrigeration. To facilitate research in this emerging paradigm, we have established the Materials Hub with Three‐Dimensional Structures (MatHub‐3d) repository, which serves as the foundation for high‐throughput (HTP) calculations, property analysis, and the design of thermoelectric materials. In this review, we summarize recent advancements in thermoelectric materials powered by the MatHub‐3d, specifically HTP calculations of transport properties and material design on key factors. For HTP calculations, we develop the electrical transport package for HTP purpose, and utilize it for materials screening. In some works, we investigate the relationship between transport properties and chemical bonds for particular types of thermoelectric compounds based on HTP results, enhancing the fundamental understanding about interested compounds. In our work associated with material design, we primarily utilize key factors beyond transport properties to further expedite materials screening and speedily identify specific materials for further theoretical/experimental analyses. Finally, we discuss the future developments of the MatHub‐3d and the evolving directions of database‐driven thermoelectric research.

NANOBIOTECHNOLOGY INTERVENTION TO ENHANCE POST HARVEST SHELF LIFE OF FRUIT CROPS

The increasing human population creates the demand quality food for health on the globe. Moreover, there is wastage of agricultural commodities like highly perishable fruits during post-harvest management via different channel points from farms to consumers. Therefore, there is a need for some alternative, cost-effective, efficient, green and eco-friendly technology to reduce post-harvest losses of fruit crops, especially for climacteric nature. Meanwhile, nanotechnology can provide a great solution of active, smart and antimicrobial activity-based nano packaging for safe transport and less deterioration of fruit quality during the long-distance market. In the present review, cum short communication will discuss some case studies in brief with reported analysis. Moreover, the biotechnological approach of gene expression at the molecular and cellular level is add insight into delaying in ripening of fruits due to nanotechnology.

Demonstration of the avoidance of brittle fracture of a radioactive material transport package during an impact event

The stress-based assessment described in BS7910:2019 for the demonstration of avoidance of fracture initiation has been applied to a radioactive material transport package. The transport package was designed and manufactured in the early 1990s, predating modern regulatory requirements that are more prescriptive to satisfy the avoidance of brittle fracture. The package design can be usefully re-purposed for the transport of low/intermediate level waste - such as that produced in prototype fission reactors. Current regulations may require demonstration of the avoidance of brittle fracture for this type of package at -40°C in a fault condition -which, for this package, is considered as an impact from a 1.2m drop height. This paper presents an overview of the demonstration of the package, explaining the process of identifying transient stresses throughout the package and then focusses on treatment of high stresses in the base of the package. Stress classification into primary and secondary stresses is discussed. It is demonstrated that such stresses are permissible by extrapolating from solutions in BS7910:2019 Annex N using cracked body models and taking advantage of low constraint conditions at the crack tip.

Marketing in the Era of Data Change

If we do not carry out the construction of modern system and without the help of informatization, it will not only waste time, but also be prone to errors. Using information technology, we can achieve three scientific and modern requirements. One is scientific process. Through information technology, all links of sorting, sorting, and receiving, distribution and transportation packaging are implemented in place, and automatic scanning instrument is used to ensure that the products are free from pollution, odor and wrong taking, and the one-stop process service is realized. The second is scientific operation, through information technology to integrate the collaborative supply chain, constantly analyze and improve their own problems, learn from each other to realize integrated supply, real-time information sharing, and promote all aspects of logistics into a higher level. Similarly, in this process, enterprises are no longer simply playing the role of logistics, but also should be introduced into modern science and technology industry, establish research bases within logistics, introduce information facilities, and contribute to the promotion of corporate culture.

Modeling package delivery acceptance in Crowdshipping systems by Public Transportation Passengers: A latent class approach

The subject of this research is to model the probability of accepting package delivery tasks in Crowd-Shipping (CS) systems focusing on shipping packages by Public Transportation (PT) passengers. Real-world implementation of such a PT-based CS initiative requires a proper grasp of the behavior of crowd shippers, package receivers, and senders, among which crowdshippers are at the center of attention. Given survey data collected from 2,208PT passengers in the Sydney metropolitan area, this study constructs a model for package delivery task acceptance among PT passengers who express a willingness to participate as crowdshippers. A Latent Class (LC) choice model is developed and estimated to explore different classes of participant characteristics and preferences for accepting CS delivery tasks, under different levels of offered incentive, package weight, and required detour distance at the destination. As a key finding, the model identifies three classes, namely “leisurely”, “avid”, and “skeptical” users with class sizes of 19%, 53%, and 28%, respectively. Leisurely users tend to be majorly employed with relatively higher ages and lower PT trip frequency per month. This class shows a potential desire to take CS tasks as long as they are not logistically burdensome. Avid users, forming the largest class of the population, are mostly younger PT passengers who are less sensitive to task difficulty and might accept even CS tasks with minimum incentives (around AU$3). Skeptical users, displaying high PT trip frequency per month and high income, are unwilling to accept the CS tasks unless get compensated well.

Recycled or reusable: A multi‐method assessment of eco‐friendly packaging in online retail

AbstractThe rapid growth of online retail increases the demand for packaging. Although packaging is necessary to fulfill logistic and marketing functions, it fosters the depletion of resources, is often used carelessly, and thus negatively impacts the environment. Eco‐friendly packaging variants could provide a solution to this problem. Since many stakeholders must be involved to promote their use, this study develops a conceptual framework that reconciles their different perspectives and combines these with an environmental assessment to facilitate the transition to more sustainable online retail. We apply a multi‐method research approach to investigate the different views. We use qualitative interviews and website analyses to capture the perspective of online retailers, conduct an online survey (n = 1491) to investigate consumers’ perceptions of various product and transport packaging alternatives, and perform a life cycle assessment (LCA) of these options. The findings reveal that online retailers lack knowledge regarding consumer preferences and the environmental impact of packaging. The consumer survey shows a strong preference for packaging made from recycled paper and general avoidance of plastic packaging. The LCA results reveal that recycled and reusable variants are environmentally beneficial. The findings are interpreted in light of the relationships assumed in the conceptual framework. From a theoretical perspective, our results indicate that online retailers are concerned about the signaling role of packaging and that consumers refer to heuristic cues when deciding between packaging variants. We reconcile the different perspectives to propose strategies that contribute to a broader distribution of eco‐friendly packaging in online retail.

Establishing best practices for E-commerce transport packaging waste management in Canada: A systematic review

The growth in online retail purchases has increased significantly, especially through the COVID-19 pandemic, yet causes more packaging waste than brick-and-mortar retail. Free and easy returns further exacerbate the problem. Current research addressing post-consumer packaging waste has focused on packaging design and material choices. Yet, effective guidelines, policies, strategies, and practices for e-commerce packaging waste management must be determined (Escursell et al., 2021). Therefore, this research identifies global best practices to address transport packaging waste in e-commerce, focusing on Canada. A systematic review of the extant literature (2011–2020) revealed five key objectives of packaging sustainability guidelines: Optimizing Resources, Responsible Sourcing, Resource Recovery, Material Health, and Consumer Engagement. The analysis showed that Responsible Sourcing and Resources Recovery were highlighted in 41% of publications, Optimizing Resources in 31%, and Consumer Engagement in 23% of the studies. The most popular waste reduction strategy was Design for Environment under the Optimizing Resources guideline. This work is the first to identify and articulate clear guidelines, policies, and practices to support industry and policy decision-makers in addressing the transport packaging waste problem in e-commerce.

Lead and Zinc Groundwater Contaminant Transport Modelling Using MT3DMS in Xaysomboun Province, Lao PDR

Contaminant transport modelling is commonly applied in the Groundwater Modelling System (GMS). Modular Three-Dimensional Multispecies Transport (MT3DMS) package is one of other packages, developed by the U.S. Geological Survey, this research presents the employing of the M3TDMS package as excellent tools to establish the 3D conceptual model of contaminant transport modeling, simulate and predict the multispecies of Lead and zinc substances which transport in the groundwater, there are 15 boreholes that were observed and monitored, the results of the contaminant transport modeling was found the Lead(Pb) contaminant transport with initial concentrations of 3.96 mg/l at borehole MB48 as point source, the concentration reduced to 0.1 mg/l, after 3,650 days simulation. The initial zinc (Zn) concentration of 0.886 mg/l at borehole CV04 decreases to 0.023 mg/l after 3,650 days simulation.

Data analysis of simulated fuel-loaded sea transportation tests under normal conditions of transport

In this study, to evaluate the shock and vibration load characteristics of used fuel, a sea transportation test was conducted using simulated fuel assemblies under normal transport conditions. An overall test data analysis was performed based on the measured strain and acceleration data obtained from cruise, rotation, acceleration, braking, depth of water, and rolling tests. In addition, shock response spectrum and power spectral densities were obtained for each test case. Amplification and attenuation characteristics were investigated based on the load path. The load was amplified as it passed from the overpack to the simulated used fuel-assembly. As a result of the RMS trend analysis, the fuel-loading position of the transportation package affected the measured strain in the fuel rod, and the maximum strains were obtained at the spans with large spacing. However, even these maximum strains were very small compared to the fatigue strength and the cladding yield strength. Moreover, the fuel rods located on the side exhibited a larger strain value than those at the center.

A personalized Monte Carlo study of tumor and critical organ doses for Trans-arterial Radioembolization patients.

Trans-arterial Radioembolization (TARE) is an intra-arterial treatment method for liver malignancies. In this procedure, the therapeutic tumor dose is significant for predicting the treatment effectiveness while the dose absorbed in an organ at risk provides an understanding of its tolerance to radiation. This study proposes a Monte Carlo (MC) approach for determining absorbed organ doses for patients undergoing TARE treatment. The technique is based on the use of a voxel-based partial body model generated for each patient from his/her anatomical image data to represent the critical body structures more realistically. These structures are first segmented from image slices to create an image block which is then incorporated into a radiation transport package (MCNP6.2) to perform MC simulations. When used along with the parameters specific to a patient's treatment, such as lung-shunt factor (LSF), tumor-to-normal liver ratio (TLR), fractional uptakes, and administered activity, this approach allowed more accurate simulation of radiation interactions and hence provided absorbed doses specific to a TARE patient. The MC method also calculated the absorbed doses in organs or tissues that were close to target tissues for which the MIRD formalism makes no predictions. MIRD calculations were found to overestimate the absorbed doses by as much as 11% in lungs, 5% in liver, and 20% in tumor volumes. This raises concerns about the treatment's efficacy when estimating the correct activity to be administered to a patient. When each patient simulation was repeated with a 90Y source spectrum to reflect the distribution of varying beta energies, the liver and the lungs were observed to receive relatively lower doses than those obtained with monoenergetic beta particles. Thus, it can be stated that the approach adopted in this study offers a more precise model of the patient's critical tissues and serves as a personalized dosimetric tool for TARE treatment planning.

Investigations of aged metal seals for transport package safety assessment

Abstract. Acceptable limits for activity release from transport casks for high-level radioactive material specified in the IAEA regulations must be kept by the integrity of cask body and the cask sealing system. BAM – the German competent authority for mechanical, thermal and containment assessment of packages liable for approval – verifies the activity release compliance with the regulatory limits. One of the fundamental aspects in assessment is the specification of conservative package design leakage rates. To ensure the required package tightness for both storage and transport of the cask before and after storage, usually metal seals of the HELICOFLEX® type are used. Due to long-term use, the seal behaviour is influenced by temperature and time. The mechanical and thermal loadings associated with the routine, normal and accident conditions of transport specified in the regulations can have a significant effect on the leak tightness of the sealing system. Whereas the safety for application of new, non-aged HELICOFLEX® seals is verified sufficiently, there are still technical data gaps concerning the efficiency of aged HELICOFLEX® seals. BAM performed experiments to learn more about the sealing efficiency of aged HELICOFLEX® seals with aluminium and silver outer jackets. The seals were compressed in test flanges, and for artificial ageing the complete flange systems were stored in an oven for several months at a high temperature. During the compression and decompression tests after the ageing, load-deformation characteristics of the seals and leakage rates were measured. With these tests a load situation was simulated, which can occur in the regulatory drop test of the cask: under high-impact loads the bolted lid can lift a little for a short moment, allowing a little movement of the seal so that the contact area can change before compressing again. The poster presentation will show details about test conditions and first results.