Resource Utilization Techniques Research Articles

Analyzing strain localization of Chang'E-5 lunar regolith through discrete element analysis

The current understanding of the geotechnical behavior of lunar in-situ resources, particularly lunar regolith (LR), is significantly limited due to its scarcity. To address this gap, this research utilized the morphological characteristics of LR particles obtained from the Chang'E-5 (CE-5) mission to construct numerical simulants using the discrete element method (DEM). This approach was then employed to investigate the mechanical properties of LR. Firstly, high-definition lunar particle images from the CE-5 mission were selected to capture the morphological characteristics and grain size distribution. These morphological characteristics were linked with the rolling resistance parameter and incorporated into the three-dimensional (3D) micromechanical contact model. Additionally, a flexible boundary condition was employed in the triaxial simulation to ensure the evolution of strain localization. The relative particle translation gradient (RPTG) concept was utilized to capture the onset and development of strain localization during the shear process. The results indicated that the numerical lunar simulants can effectively reproduce the mechanical response of LR. Furthermore, at the particle scale, particle shape characteristics play a crucial role in particle rotation and translation during the shear process. This study may establish a foundation for lunar resource exploration and utilization techniques.

Development and performance evaluation of sunflower straw cellulose ether ecological sand-fixing material

Sunflowers are widely cultivated as a cash crop in the Inner Mongolia Autonomous Region, China. However, due to the lack of efficient resource utilization techniques, most of the sunflower stalks are discarded. In the Hetao irrigation area, the problem of desertification has prompted the limited use of sunflower straw to construct physical sand barriers for windbreaks and sand stabilization. In response to this, this study focuses on synthesizing a cellulose ether sand-fixing material using sunflower straw, the primary agricultural waste in Denkou County, Hetao irrigation district. This material enhances the effective adhesion between sand grains, reduces porosity among loose sand grains, and inhibits sand grain movement. The findings from this study conclusively demonstrate that the sand-fixing materials under investigation meet international standards for mechanical properties. They effectively transform loose, unconnected sand grains into a state with strong adhesion properties.

Optimizing makespan and resource utilization in cloud computing environment via evolutionary scheduling approach.

As a new computing resources distribution platform, cloud technology greatly influenced society with the conception of on-demand resource usage through virtualization technology. Virtualization technology allows physical resource usage in a way that will enable multiple end-users to have similar hardware infrastructure. In the cloud, many challenges exist on the provider side due to the expectations of clients. Resource scheduling (RS) is the most significant nondeterministic polynomial time (NP) hard problem in the cloud, owing to its crucial impact on cloud performance. Previous research found that metaheuristics can dramatically increase CC performance if deployed as scheduling algorithms. Therefore, this study develops an evolutionary algorithm-based scheduling approach for makespan optimization and resource utilization (EASA-MORU) technique in the cloud environment. The EASA-MORU technique aims to maximize the makespan and effectively use the resources in the cloud infrastructure. In the EASA-MORU technique, the dung beetle optimization (DBO) technique is used for scheduling purposes. Moreover, the EASA-MORU technique balances the load properly and distributes the resources based on the demands of the cloud infrastructure. The performance evaluation of the EASA-MORU method is tested using a series of performance measures. A wide range of comprehensive comparison studies emphasized that the EASA-MORU technique performs better than other methods in different evaluation measures.

Material aspects of sintering of EAC-1A lunar regolith simulant

Future lunar exploration will be based on in-situ resource utilization (ISRU) techniques. The most abundant raw material on the Moon is lunar regolith, which, however, is very scarce on Earth, making the study of simulants a necessity. The objective of this study is to characterize and investigate the sintering behavior of EAC-1A lunar regolith simulant. The characterization of the simulant included the determination of the phase assemblage, characteristic temperatures determination and water content analysis. The results are discussed in the context of sintering experiments of EAC-1A simulant, which showed that the material can be sintered to a relative density close to 90%, but only within a very narrow range of temperatures (20–30 °C). Sintering experiments were performed for sieved and unsieved, as well as for dried and non-dried specimens of EAC-1A. In addition, an analysis of the densification and mechanical properties of the sintered specimens was done. The sintering experiments at different temperatures showed that the finest fraction of sieved simulant can reach a higher maximum sintering temperature, and consequently a higher densification and biaxial strength. The non-dried powder exhibited higher densification and biaxial strength after sintering compared to the dried specimen. This difference was explained with a higher green density of the non-dried powder during pressing, rather than due to an actual influence on the sintering mechanism. Nevertheless, drying the powder prior to sintering is important to avoid the overestimation of the strength of specimens to be fabricated on the Moon.

Laser melting manufacturing of large elements of lunar regolith simulant for paving on the Moon

The next steps for the expansion of the human presence in the solar system will be taken on the Moon. However, due to the low lunar gravity, the suspended dust generated when lunar rovers move across the lunar soil is a significant risk for lunar missions as it can affect the systems of the exploration vehicles. One solution to mitigate this problem is the construction of roads and landing pads on the Moon. In addition, to increase the sustainability of future lunar missions, in-situ resource utilization (ISRU) techniques must be developed. In this paper, the use of concentrated light for paving on the Moon by melting the lunar regolith is investigated. As a substitute of the concentrated sunlight, a high-power CO2 laser is used in the experiments. With this set-up, a maximum laser spot diameter of 100 mm can be achieved, which translates in high thicknesses of the consolidated layers. Furthermore, the lunar regolith simulant EAC-1A is used as a substitute of the actual lunar soil. At the end of the study, large samples (approximately 250 × 250 mm) with interlocking capabilities were fabricated by melting the lunar simulant with the laser directly on the powder bed. Large areas of lunar soil can be covered with these samples and serve as roads and landing pads, decreasing the propagation of lunar dust. These manufactured samples were analysed regarding their mineralogical composition, internal structure and mechanical properties.

(Invited) Zirconia-Based Hollow Anode Development for Molten Regolith Electrolysis

Molten regolith electrolysis (MRE) is a promising in-situ resource utilization technique for producing oxygen and molten metal alloys from lunar regolith. However, MRE requires operating temperatures at or above 1600°C to melt lunar regolith and dissociate the molten oxides to enable electrolysis. Anode degradation in this corrosive and oxidizing environment is a major concern for long-term operation on the lunar surface and can be mitigated by a novel hollow anode design with a solid electrolyte shell and porous metallic core as proposed here. The metallic anode will be shielded from the regolith melt by an oxygen ion-conducting zirconia-based ceramic, allowing electron transfer to occur in the interior of the shell. Additionally, bubble formation at a traditional anode surface is avoided, thereby eliminating the concerns of molten regolith splatter and increased ohmic resistance. This work focuses on corrosion studies of dense stabilized zirconia in contact with molten lunar mare and highlands regolith simulants at 1600°C to support hollow anode development. The interactions between zirconia and molten regolith are characterized using SEM/EDS, with an emphasis on elemental analysis to assess reactivity and degradation of zirconia.

Waste remediation: Low-temperature synthesis of hybrid Cu(OH)2/CuO and CuO nanostructures from spent printed circuit boards and their dye degradation studies.

The demand for environmentally friendly and sustainable resource utilization techniques for recycling waste printed circuit boards is significant due to their status as valuable secondary resources, containing high-purity copper and precious metals. In this context, Cu(OH)2/CuO and CuO nanostructures were fabricated using alkaline precipitation and low-temperature aging methods using the strip solution originated from laboratory-scale spent mobile phone printed circuit board recovery process. XRD, FTIR, FESEM-EDX, and TEM were utilized to characterize the as-recovered nanoproducts. A hybrid structure of Cu(OH)2/CuO was formed at 70°, and monoclinic CuO phase was formed at 80°C aging time. The results show that Cu(OH)2/CuO nanoflakes have an average crystallite size of 24.06nm and a particle width of 22 ± 3nm. Cu(OH)2/CuO nanoflakes formed at 70°C aging temperature and 24-h residence time have finer crystallite and particle sizes than CuO-ridged nanospheres formed at 80°C aging temperature. The optical band gap energy of Cu(OH)2/CuO and CuO nanostructures formed was found to be 2.28eV and 2.22eV, respectively. The hybrid Cu(OH)2/CuO nanostructure photocatalyzed the decomposed 97.28% rhodamine blue using a visible light source, whereas the CuO nanostructure degraded only 14.64% rhodamine blue dye under similar conditions. A surfactant-less hybrid structure is developed without the use of any chemical precursor. Thus, a high value-added product is produced using one waste material to remove another waste in wastewater treatment.

Phosphorus recovery and resource utilization from phosphogypsum leachate via membrane-triggered adsorption and struvite crystallization approach

Phosphorus pollution from phosphogypsum (PG) leachate has caused severe problems in the water environment and ecology. Efficient phosphate recovery and resource utilization techniques are crucial as they can aid the phosphorus pollution problem and recover the scarcity of phosphorus resources. Herein, we developed a highly efficient phosphorus recovery strategy from PG leachate by integrating the ZrO2 membrane-triggered adsorption technique with the struvite crystallization process. More than 89.23% of the phosphorus anions in the PG leachate can be recovered via membrane-triggered adsorption. With the concentrated phosphate anions washed from membrane adsorption, the phosphate anions can be further employed for struvite crystallization, and an overall phosphorus recovery efficiency of 59.36% can be achieved. The obtained fine struvite product is of high purity, with NH4MgPO4·6H2O weight ratio of up to 89.83%. The novel strategy developed here demonstrates a green and sustainable strategy toward phosphorus recovery from the PG or PG-polluted groundwater or surface water leachate, which could be applied to practical phosphorus recovery and struvite fertilizer production. The commercialization of this strategy will shed light on the emergency PG pollution control at the YangtzeRiver upstream area.

Nexus among financial innovation, natural resources and economic recovery: A fresh empirical insight from China

The relationship between natural resources, technological innovation and economic development has been debated. Macroeconomic elements like green development and technological may be crucial in attaining ecological sustainability in the context of eco-innovation since climate change is the main issue of contemporary research. As a result, this research uses data from 2000 to 2020 to evaluate the dynamic relationship between natural resources, financial innovation, and economic progress in China. We used the ARDL model to confirm the long-term, consistent relationship between ecological sustainability and natural resources and technological advancements. However, there is evidence that natural resource interaction positively influences economic development. Based on empirical findings, we recommend innovative methods of development together with effective management techniques for the productive utilization of natural resources for sustainable management.

An IoT-based resource utilization framework using data fusion for smart environments

Nowadays, many communities are emerging towards smart environments, requiring the communication and collaboration of diverse Internet-of-Things (IoT) devices. A smart environment exploits the use of IoT technology to share and process data among such devices for a better living. However, this comes with additional costs, such as the exponential growth of IoT devices, the heterogeneity of IoT use cases, and the new complex features encountered by IoT data, which complicate their processing and analysis using the traditional techniques. This causes a dramatic performance degradation of the used processing resources, which directly affects the overall efficiency and performance of IoT-based systems. Although different studies have presented resource utilization approaches for IoT systems, but they were not evaluated from different resource utilization perspectives. Besides, no efforts have been directed to investigate their effectiveness to process the unprecedented IoT data features that inevitably impact the accuracy and efficiency of resource utilization. In this paper, the Triple Phases Resource Utilized Data Fusion (TPRUDF) framework is proposed as the first IoT-based cost-aware resource utilization using data fusion. It exclusively considers different IoT data features by employing three phases of data fusion: (1) data in – data out, (2) data in – feature out, and (3) feature in – decision out. TPRUDF fuses the raw IoT data by maintaining the complex IoT data features, independent of the IoT domain or the computing model, using the spatiotemporal data fusion (STDF) IoT-based data fusion approach. TPRUDF then fuses the uncorrelated data features via the Principal Component Analysis. Finally, it employs two different resource utilization techniques: (1) Genetic Algorithms and (2) Particle Swarm Optimization, fusing their results using the voting logic fusion technique. A public edge-computing simulator is used to evaluate TPRUDF via three real-world smart cities datasets. The experimental results of the proposed TPRUDF framework indicate that it: (1) achieves an average accuracy level of resource utilization equal to 91%, (2) increases the resource utilization throughput by an average of 40% and eventually minimizes the processing delay, (3) boosts the resource utilization availability by 60%, and (4) decreases the energy consumption by 35%.

Architectural impacts of in-situ resource utilization production of oxygen for use as propellant in a Mars ascent vehicle

NASA is in the processes of evaluating various architectures that may support human missions to Mars. A multitude of concepts are being traded and associated sensitivities are being analyzed. Among these trades, several options for Mars Ascent Vehicle (MAV) propellant supply are being considered. Due to mass constraints on the Mars descent system and the in-space transportation system, landing a fully fueled MAV, that can launch humans from the surface of Mars, presents significant integrated architecture challenges. Consequently, MAV propellant must either be pre-positioned and transferred across the surface robotically or made on the surface via In-Situ Resource Utilization (ISRU) techniques. In each case, there are implications to the number of architecture elements, total system mass, power requirements, complexity of operations, and required technology developments. An analysis that compares an ISRU point solution to a similar point solution that pre-positions and transfers propellant is detailed.

Quantification and Consumption Pattern of Fuel Wood in Mornaula Reserve Forest in Kumaun, Indian Himalaya: Implication for Sustainability and Conservation

Present study provides information on biomass utilization, fuel wood species diversity, their regeneration status, and impact of fuel wood harvesting in Mornaula Reserve Forest (MRF) in Kumaun, India. A total of 34 plant species (32 trees and 2 shrubs) were collected by the inhabitants for fuel, belonging to 22 families, dominated by Rosaceae (04 species) followed by Pinaceae and Lauraceae (02 each). Distribution of plant species ranges from1500-2200 in a wide range of habitats, forests being the most preferred one. High preference and Resource Use Index of Quercus leucotrichophora, Quercus floribunda , and Rhododendron arboreum, Pinus roxburghii, Myrica esculenta, Symplocos chinensis, and Cedrus deodara as fuel indicated high pressure on these species. The continuous exploitation of these species from the MRF may lead to rapid deletion of their population. Therefore, adequate conservation measures have to be taken to maintain the current status of the habitats, species and communities for the effective management of the MRF. Awareness among the villagers needs to be created for the resource utilization techniques, so that sustainable utilization of the species could be done by the villagers. Further, the degraded forests may be re-established through plantations of the seedlings of the preferred fuel wood species with the participation of local inhabitants.

An efficient resource utilization technique for scheduling scientific workload in cloud computing environment

<span lang="EN-US">Recently, number of data intensive workflow have been generated with growth of internet of things (IoT’s) technologies. Heterogeneous cloud framework has been emphasized by existing methodologies for executing these data-intensive workflows. Efficient resource scheduling plays a very important role provisioning workload execution on Heterogeneous cloud framework. Building tradeoff model in meeting energy constraint and workload task deadline requirement is challenging. Recently, number of multi-objective-based workload scheduling aimed at minimizing power budget and meeting task deadline constraint. However, these models induce significant overhead when demand and number of processing core increases. For addressing research problem here, the workload is modelled by considering each sub-task require dynamic memory, cache, accessible slots, execution time, and I/O access requirement. Thus, for utilizing resource more efficiently better cache resource management is needed. Here efficient resource utilization (ERU) model is presented. The ERU model is designed to utilize cache resource more efficiently and reduce last level cache failure and meeting workload task deadline prerequisite. The ERU model is very efficient when compared with standard resource management methodology in terms of reducing execution time, power consumption, and energy consumption for execution scientific workloads on heterogeneous cloud platform.</span>

Energy‐aware autoscaling for scientific workflow in cloud environment

SummaryThe devices used for information and communication purpose consume an increasing amount of energy. As a result, the datacenters consume a lot of energy. Due to the expanding use of cloud services, there is considerable interest in reducing the energy consumption of datacenters. Effective resource utilization techniques and reduction in energy consumption are two crucial metrics in today's cloud computing environment. Many issues come along with contradicting objectives, viz., minimizing energy consumption raising the expenses of service supply. Autoscaling features of the cloud can bundle these issues. The major hurdle for effective resource scalability is the lack of proper management of energy supply to devices of servers in the datacenter. The main objective of the article is to supply energy to devices as per the allocated job‐size on the interaction of complex energy, to increase the energy utilization of servers. Also, using renewable energy (RE) to supplement the operational energy of the cloud datacenter. In this direction, the article presents a predator‐prey‐based mathematical model for energy scaling that leverages the accessibility of RE source to decrease the high energy demands of the datacenter. It is formalized using ecological concepts of metabolism and allometric scaling. An allometric energy scaling (AES) algorithm is presented. The performance and evaluation of the proposed algorithm are implemented with the Cloudsim 4.0 simulator. The results are compared with the HEFT algorithm, and AES algorithm gives slightly better results in the case of optimum energy consumption and processing cost compared with the HEFT algorithm.

Energy Aware Resource Utilization Technique for Workflow Scheduling in Cloud Computing Environment

Heterogeneous multicore computational environment are increasingly being used for executing scientific workload. Heterogeneous computational framework aid is reducing energy dissipation for executing real-time data intensive workload by employing Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS). However, reducing energy and improving performance is becoming major constraint in modelling workload scheduling model in heterogeneous computational environment. Recently, number of multi-objective based workload scheduling aimed at minimizing power budget and meeting task deadline constraint. However, these model induce significant overhead when demand and number of processing core increases. For addressing research problem this work assume that different task will have different execution path, I/O access, memory, active processing, and cache requirement. Thus, this paper present Energy Aware Resource Utilization (EARU) model by minimizing energy dissipation and utilizing cache resource more efficiently. The EARU model achieves much lesser execution time, energy consumption, and power consumption when compared with existing multi-objective based and DVFS-based workload scheduling algorithm.

An energy optimization with improved QOS approach for adaptive cloud resources

In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques.

Green Cloud Computing Strategies for Load Balancing

Cloud computing nowadays has emerged as one of the important aspect to distributed computing. Organizations are adopting cloud computing (Escalnte, D. and Korty, A.J., 2011. Cloud services: Policy and assessment. EDUCAUSE Review 46(4).) for performance upgrading as one of parameter and also for cost effective computing. In same context to increase resource utilization and energy efficient techniques are developed using green cloud. These green datacenters provide overall efficiency to cloud database and thereby will be beneficial to distribute load to virtual machines. Green cloud therefore provides environmental benefits by reducing energy consumption by creating virtual machines and balancing there load. This paper will include detailed review for various load balancing strategies as algorithm which are applicable in any environment with respect to cloud and variety of parameter for load balancing.

Round Robin Based Efficient Resource Allocation and Utilization in an Organization

In an organization, resource allocation to a request is a complex task. Traditionally, resource allocation is done through manually with high time consumption. Similarly, collision is occurring for allocating a single resource to multiple requests. Thus, leads to complex problems and slow-down the working process. The existing resource allocation technique, allocate resources continuously to a specific request and omit another request. This kind of allocation technique also leads to lots of critical issues. That is the non-allocated process never gets a resource. To overcome these issues, the Round Robin based Resource allocation and Utilization technique is proposed in this work. The Round Robin technique allocates resources to the request in an efficient with equal priority. Similarly, the proposed technique reduces collision and takes less time for mapping a resource with a request. The experimental results shows improved accuracy than the traditional resource allocation technique.

FaaVPP: Fog as a virtual power plant service for community energy management

The fossil fuel based power generators emit CO2 and expensive electricity. In this paper, fog as a virtual power plant (FaaVPP) is proposed to integrate power of distributed renewable power generators and the utility for a community. A prosumer–consumer and service providing company oriented linear model is proposed to minimize power consumption cost for prosumers and maximize profit for the company. The mathematical proof of linear model validates the significance for service provider and energy users. Moreover, outcome of case studies advocate the efficiency of the model. Efficient resource utilization techniques of fog resources ensure the near-real time service provision to the community. In the paper, effects of resource utilization techniques e.g., processing time (PT), response time (RT), computing cost and energy consumed by the resources are also analyzed.

Earth's Minimoons: Opportunities for Science and Technology

(modified from published version) Twelve years ago the Catalina Sky Survey discovered Earth's first known natural geocentric object other than the Moon, a few-meter diameter asteroid designated 2006 RH120. Despite significant improvements in ground-based telescope and detector technology in the past decade the asteroid surveys have not discovered another temporarily-captured orbiter (TCO; colloquially known as minimoons). Within a few years the Large Synoptic Survey Telescope (LSST) will either begin to regularly detect TCOs or force a re-analysis of the creation and dynamical evolution of small asteroids in the inner solar system. The first studies of the provenance, properties, and dynamics of Earth's minimoons suggested that there should be a steady state population with about one 1- to 2-meter diameter captured objects at any time. That model was then improved and extended to include the population of temporarily-captured flybys (TCFs), objects that fail to make an entire revolution around Earth while energetically bound to the Earth-Moon system. Several different techniques for discovering TCOs have been considered but their small diameters, proximity, and rapid motion make them challenging targets for existing ground-based optical, meteor, and radar surveys. We expect that if the TCO population is confirmed, and new objects are frequently discovered, they can provide new opportunities for 1) studying the dynamics of the Earth-Moon system, 2) testing models of the production and dynamical evolution of small asteroids from the asteroid belt, 3) rapid and frequent low delta-v missions to multiple minimoons, and 4) evaluating in-situ resource utilization techniques on asteroidal material. Here we review the past decade of minimoon studies in preparation for capitalizing on the scientific and commercial opportunities of TCOs in the first decade of LSST operations.