Designs and applications of the rotary limaçon compressors and expanders - a review
- Authors: Belfiore, Christopher , Lu, Kui , Phung, Truong , Sultan, Ibrahim
- Date: 2022
- Type: Text , Conference paper
- Relation: 3rd International Conference on Energy and Power, ICEP 2021, Chiang Mai, Thailand, 18-20 November 2021, AIP Conference Proceedings Vol. 2681
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- Description: Limaçon machines are positive displacement fluid processing machines that belong to the rotary machine family. The limaçon machines can be utilized as expanders to extract work from the working fluid or as compressors to provide energy to the working fluid. The main components of the limaçon machine that are directly involved in fluid processing are the housing and rotor, the construction of which are of either limaçon of Pascal curves or circular curves. One distinct feature of the limaçon machine is the limaçon motion of the rotor; the rotor rotates about and slides along a pole, o, inside a housing during the machine operation. Of important note is the motion of the machine rotor inside the housing always follows the limaçon motion irrespective of their profiles. In this paper, different designs and embodiments of the limaçon machine and their advantages and disadvantages have beed discussed, and the research has been carried out on specific applications, i.e., expander and compressor including the work done on fluid induction, sealing and leakages, porting, and inlet and outlet valve control of such machines. © 2022 American Institute of Physics Inc.. All rights reserved.
Developing a framework for generating realistic, but not real, synthetic maintenance records
- Authors: Larkins, Jo-Ann , Chattopadhyay, Gopinath , Morey, Stephen
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022, Anand, India, 12-15 December 2022, 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022
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- Description: Informed decisions for life-extension of complex long-life assets require knowledge of the current state of the asset as well as understanding of its maintenance and failure history. A lack of access to sufficient and reliable data for method validation, such as appropriately detailed maintenance logs, inhibits research into better-informed decisions for life-extension of long-life capital-intensive assets. Researchers must negotiate industry partnerships and overcome barriers to data access due to commercial sensitivities. This paper proposes a conceptual framework for generating realistic, but not necessarily real, synthetic maintenance records. Maintenance logs have strong structural synergies with electronic health records. We adapt and map methods for generating synthetic health records using only publicly available data sources to create synthetic maintenance records. Facet strings are used to construct a probabilistic framework for developing brief free notes. The generation of realistic synthetic maintenance records can be achieved using publicly available data, supported by expert engineering knowledge of the design and maintenance of the system. © 2022 IEEE.
Development of architecture of autonomous hydraulic rock breaker for limestone mines
- Authors: Sinha, Aryan , Vasan, Sabari , Nandrekar, Job , Aditya, Umang , Khandelwal, Manoj , Prasad, Naresh , Bhatawdekar, Ramesh , Rathinasamy, Vynotdni
- Date: 2022
- Type: Text , Conference paper
- Relation: International Conference on Geotechnical challenges in Mining, Tunneling and Underground structures, ICGMTU 2021, Virtual, online, 20-21 December 2021, Lecture Notes in Civil Engineering Vol. 228, p. 683-695
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- Description: Boulders which are generated during primary blasting are required to undergo secondary blasting prior to crusher operation. Hydraulic rock breaker is one of the techniques which is being utilized to break boulders instead of secondary blasting. This study aims to develop an architecture of AI model for rock breakers with autonomous remote operation. Firstly, several technical specifications of various rock breakers mounted on 30 T class hydraulic rock breakers were evaluated. Also, the factors affecting cost and operation were identified and discussed. Later, the autonomous rock breaker installed on the crusher hopper at a site in Australia was reviewed as global technological advancement. Based on the review, a five-stage architecture for developing autonomous hydraulic rock breaker was developed. The factors affecting the cost of hydraulic excavator and rock breaker can be classified into direct and indirect cost. The direct cost includes operational cost such as oil, replacement of chisel and bucket teeth and wages as well as maintenance cost. Meanwhile, the indirect cost is related to site issues such as locating boulder, boulders jamming crusher, waiting dozer to push boulder, etc. Also, the factors influencing operation of hydraulic hammer shall be classified into very important (i.e. oil flow, chisel diameter), important (i.e. elasticity, impact rate) and desirable (i.e. hardness, chisel length). The five stages architecture for developing autonomous hydraulic rock breaker are development, data collection, data pre-processing, model deployment and model testing. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Digital twin mobility profiling : a spatio-temporal graph learning approach
- Authors: Chen, Xin , Hou, Mingliang , Tang, Tao , Kaur, Achhardeep , Xia, Feng
- Date: 2022
- Type: Text , Conference paper
- Relation: 23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021, Hainan, China, 20-22 December 2021, Proceedings 2021 IEEE 23rd International Conference on High Performance Computing & Communications, 7th International Conference on Data Science & Systems 19th International Conference on Smart City 7th International Conference on Dependability in Sensor, Cloud & Big Data Systems & Applications p. 1178-1187
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- Description: With the arrival of the big data era, mobility profiling has become a viable method of utilizing enormous amounts of mobility data to create an intelligent transportation system. Mobility profiling can extract potential patterns in urban traffic from mobility data and is critical for a variety of traffic-related applications. However, due to the high level of complexity and the huge amount of data, mobility profiling faces huge challenges. Digital Twin (DT) technology paves the way for cost-effective and performance-optimised management by digitally creating a virtual representation of the network to simulate its behaviour. In order to capture the complex spatio-temporal features in traffic scenario, we construct alignment diagrams to assist in completing the spatio-temporal correlation representation and design dilated alignment convolution network (DACN) to learn the fine-grained correlations, i.e., spatio-temporal interactions. We propose a digital twin mobility profiling (DTMP) framework to learn node profiles on a mobility network DT model. Extensive experiments have been conducted upon three real-world datasets. Experimental results demonstrate the effectiveness of DTMP. © 2021 IEEE.
Discrete cosine basis oriented motion modeling with cuboidal applicability regions for versatile video coding
- Authors: Ahmmed, Ashek , Hamidouche, Wassim , Lambert, Andrew , Pickering, Mark , Murshed, Manzur
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Picture Coding Symposium, PCS 2022, San Jose, Costa Rica, 7-9 December 2022, 2022 Picture Coding Symposium, PCS 2022 - Proceedings p. 337-341
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- Description: The relentless expansion of video based applications is underpinned by video coding technologies. The latest video coding standard i.e. versatile video coding (VVC) can provide superior compression performance than its predecessors. In this regard, motion modeling plays a central role. Experimental results showed that the discrete cosine basis oriented motion model can describe complex motion better than an affine motion model, adopted in the VVC. Hence, in this paper we propose to augment the VVC motion modeling technique with a set of discrete cosine basis oriented motion models and the applicability region of each such motion model is determined by non-overlapping rectangular regions, known as cuboids. Experimental results show a bit rate savings of up to 2.37% is achievable with respect to a VVC reference. © 2022 IEEE.
Drill and blast optimisation at an underground copper-gold mine
- Authors: Guegan-Brown, Alex , Koroznikova, Larissa , Khandelwal, Manoj
- Date: 2022
- Type: Text , Conference paper
- Relation: International Conference on Geotechnical challenges in Mining, Tunneling and Underground structures, ICGMTU 2021, Virtual, Online, 20-21 December 2021, Lecture Notes in Civil Engineering Vol. 228, p. 343-354
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- Description: The process of utilising drill and blast techniques is used to improve mining performance. Drill and blast techniques have been proven to be more efficient and cost-effective compared to conventional mechanical rock breakage with machines. The degree of efficiency of the drill and blast process varies from mine to mine. These influencing factors result in drill and blast patterns that cannot be directly transposed from site to site meaning specific plans need to be developed. When creating new blast plans, unless they are created flawlessly the first-time revision or optimisation is necessary to ensure they are as efficient and effective as possible. The drill and blast patterns can be optimised to reduce the overbreak. A site specifically the current development is mining in both a weaker fragmented shale as well as moving down into a more competent granite. The optimisation will be considered for both types of ground but will have a stronger focus moving into the granite as the mine is approaching the first ore drives which are within the granite rock mass. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Dynamic mesh commonality modeling using the cuboidal partitioning
- Authors: Ahmmed, Ashek , Paul, Manoranjan , Murshed, Manzur , Pickering, Mark
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 IEEE International Conference on Visual Communications and Image Processing, VCIP 2022, Suzhou, China, 13-16 December 2022, 2022 IEEE International Conference on Visual Communications and Image Processing, VCIP 2022
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- Description: For 3D object representation, volumetric contents like meshes and point clouds provide suitable formats. However, a dynamic mesh sequence may require significantly large amount of data because it consists of information that varies with time. Hence, for the facilitation of storage and transmission of such content, efficient compression technologies are required. MPEG has started standardization activities aiming to develop a mesh compression standard that would be able to handle dynamic meshes with time varying connectivity information and time varying attribute maps. The attribute maps are features associated with the mesh surface and stored as 2D images/videos. In this paper, we propose to capture the commonality information in the dynamic mesh attribute maps using the cuboidal partitioning algorithm. This algorithm is capable of modeling both the global and local commonality within an image in a compact and computationally efficient way. Experimental results show that the proposed approach can outperform the anchor HEVC codec, suggested by MPEG to encode such sequences, with a bit rate savings of up to 3.66%. © 2022 IEEE.
Dynamic signature-based alignment factor for Var allocation
- Authors: Alshareef, Abdulrhman , Shah, Rakibuzzaman , Mithulananthan, Nadarajah , Akram, Umer , Krimanto, Uji
- Date: 2022
- Type: Text , Conference paper
- Relation: 14th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2022, Melbourne, Australia, 20-23 November 2022, Asia-Pacific Power and Energy Engineering Conference, APPEEC Vol. 2022-November
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- Description: A driven-data trajectory approach has been developed to allocate dynamic VAr source (DVS) to improve the short-term voltage stability (STVS) of power grids. The siting approach for DVS would be carried out by the comparing grid responses of different sites with DVS by considering the desired reference response. The undergoing assessment emphatically covers the full signature of grid dynamics interaction involving generation, transmission, and load characteristics. For illustration, the developed approach is applied to the Reliability and Voltage Stability (RVS) test system designed for STVS analysis. Several scenarios are tested, such as different levels of induction motor load, large-scale PV (LSPV), and LSPV reactive current injection, to demonstrate the viability and robustness of the approach. Subsequently, the viability and robustness of the siting approach are verified by checking STVS performance using the VRIsys index. © 2022 IEEE.
Effect of multiple loading rates on uniaxial compressive strength of rock
- Authors: Meerza, J. , Khandelwal, Manoj
- Date: 2022
- Type: Text , Conference paper
- Relation: 56th U.S. Rock Mechanics/Geomechanics Symposium, Santa Fe, USA, 26-29 June 2022, 56th U.S. Rock Mechanics/Geomechanics Symposium
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- Description: It is of crucial significance to study the effect of loading rate on the behaviour of rock because engineering structures are subjected to multiple loading conditions in their entire life. Although rock behaviour under single loading rate has been widely studied but very limited research has been conducted to study the performance of rock strength subjected to multiple loading conditions. This paper presents an experimental study of the effects of single and multiple strain rates on Sandstone samples. The first set of samples was tested at constant strain rates until failure to determine the peak uniaxial compressive strength (UCS). For the second set of samples, the first strain rate was applied to the sample up to a predetermined load, and then the second strain was initiated to find out the influence of multiple loading rates on the UCS of rock samples. © 2022 ARMA, American Rock Mechanics Association.
Efficient scalable 360-degree video compression scheme using 3d cuboid partitioning
- Authors: Afsana, Fariha , Paul, Manoranjan , Murshed, Manzur , Taubman, David
- Date: 2022
- Type: Text , Conference paper
- Relation: 29th IEEE International Conference on Image Processing, ICIP 2022 p. 996-1000
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- Description: Video coding techniques minimize spatial and temporal redundancies inherent in video sequences based on non-overlapping block-based image partitioning. Due to depending on the information from already encoded neighboring blocks, these algorithms lack efficient techniques to exploit the overall global redundancies. Compared to the traditional block-based coding, the cuboid coding (2D) framework has been proven to be a more effective method of image compression that exploits global redundancy by considering homogeneous pixel correlation within a frame. In this paper, we improved the idea of 2D cuboid coding to exploit both local and global redundancy from a video sequence by adopting a three-dimensional (3D) cuboid partitioning scheme for SHVC compression improvement of 360-degree videos. The proposed method considers a group of successive frames as a 3D cuboid and recursively partitions it into sub-3D cuboids where static information over a selected GOP share the same cuboid and moving regions share new cuboids with better-defined objects. All the 3D cuboids are then encoded to create a coarse representation of the video stream. Experiments indicate that the proposed framework significantly outperforms its relevant benchmarks, notably by 17.18% (average) in BD-Rate reduction and 0.82 dB in BD-PSNR gain with respect to the standard SHVC codec. © 2022 IEEE.
Embedding-based neural network for investment return prediction
- Authors: Zhu, Jianlong , Xian, Dan , Fengxiao, , Nie, Yichen
- Date: 2022
- Type: Text , Conference paper
- Relation: 2nd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology, CEI 2022, Virtual online, 23-25 September 2022, 2022 2nd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) p. 670-673
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- Description: In addition to being familiar with policies, high investment returns also require extensive knowledge of relevant industry knowledge and news. In addition, it is necessary to leverage relevant theories for investment to make decisions, thereby amplifying investment returns. A effective investment return estimate can feedback the future rate of return of investment behavior. In recent years, deep learning are developing rapidly, and investment return prediction based on deep learning has become an emerging research topic. This paper proposes an embedding-based dual branch approach to predict an investment's return. This approach leverages embedding to encode the investment id into a low-dimensional dense vector, thereby mapping high-dimensional data to a low-dimensional manifold, so that high-dimensional features can be represented competitively. In addition, the dual branch model realizes the decoupling of features by separately encoding different information in the two branches. In addition, the swish activation function further improves the model performance. Our approach are validated on the Ubiquant Market Prediction dataset. The results demonstrate the superiority of our approach compared to Xgboost, Lightgbm and Catboost. © 2022 IEEE.
Enhanced EV charging experience with an ultra-rapid charger and 800-V battery
- Authors: Li, Zilin , Cheng, Ka-Wai , Chan, Kevin , Hu, Jiefeng
- Date: 2022
- Type: Text , Conference paper
- Relation: 9th International Conference on Power Electronics Systems and Applications, PESA 2022, Hong Kong, 20-22 September 2022, Proceedings of the 9th International Conference on Power Electronics Systems and Applications, PESA 2022
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- Description: It is promising to achieve zero vehicular emissions by electricity-driven vehicles, and impressive development has been reported. Nevertheless, driving range anxiety is a long-standing issue that hinders the further public acceptance of electric vehicles (EVs). The issue is mainly caused by the driving range per full charge and long charging time, which can be addressed by increasing the charging power of EV batteries, leading to ultra-rapid DC chargers and high-voltage EV batteries. This paper is aimed to investigate the EV charging time with an ultra-rapid DC charger and 800-V battery. A two-stage charging system is first developed, including an active front-end AC-DC converter, three-phase dual active-bridge (3p-DAB), and associated controllers. The operation principles of 3p-DAB are derived with details. Then, the charging system is realized on a real-time simulator, and impacts of the charging current setting are investigated on the EV battery voltage, charging current, and charging power. Based on real-time simulation results, recharging times with different charging current settings are analyzed and compared with details. Finally, the paper is concluded with findings on the relationship between charging current, battery SoC, and total charging time. © 2022 IEEE.
Enhancing self-efficacy for fluid management in chronic kidney disease with fitbit and flex
- Authors: Oseni, Taiwo , Firmin, Sally
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Australasian Computer Science Week, ACSW 2022, Virtual, Online, 14-17 February 2022, ACM International Conference Proceeding Series p. 239-241
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- Description: Chronic kidney disease patients are required to restrict their fluid intake quite severely. Compliance is particularly challenging for many patients but failing to comply can lead to life-threatening consequences. There is some evidence that behaviour change programs based on education are effective, however a program known as Flex that is based on encouraging patients to be more adaptable and adhere less rigidly to a range of habits of daily living has not been evaluated. A core feature of the Flex program is the generation of text messages to remind patients to perform previously agreed habit changes (known as Do's) based on the analysis of Fitbit data. This study aims to apply a constructivist, qualitative methodology with a group of chronic kidney disease patients to assess the extent to which the Flex program has a positive impact on self-efficacy and ultimately on fluid management. © 2022 ACM.
Enhancing Sustainable Development on Land: Using birds of prey to disperse flocks of native birds that threaten resource use and human activities
- Authors: Wallis, Robert , Coles, Graeme
- Date: 2022
- Type: Text , Conference paper
- Relation: 28th International Sustainable Development Research Society Conference: Sustainable Development and Courage: Culture, Art and Human rights, Stockholm, 15-17 June 2022, PROCEEDINGS of the 28th Annual Conference, International Sustainable Development Research Society Conference p. 307-319
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Ensemble regression modelling for genetic network inference
- Authors: Gamage, Hasini , Chetty, Madhu , Shatte, Adrian , Hallinan, Jennifer
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2022, Ottawa Canada, 15-17 August 2022, 2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2022
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- Description: An accurate reconstruction of Gene Regulatory Networks (GRNs) from time series gene expression data is crucial for discovering complex biological interactions. Among many different approaches for inferring GRNs, there are several methods which produce high false positive interactions, and are unstable, requiring fine tuning for many of their parameters. In this paper, we consider the GRN inference problem as a regression problem, and propose a simple ensemble regression-based feature selection model which is a combination of cross-validated Lasso and cross-validated Ridge algorithms for reconstructing GRNs. Due to the novelty of the proposed ensemble model, it is able to eliminate overfitting, multi co-linearity issues, and irrelevant genes within one computational approach. While observing the type of gene-gene regulatory interactions the regression model also identifies the direction of these interactions. A new coefficient of determination (R2)-based approach identifies the best model to fit the data among LassoCV and RidgeCV, and evaluates the model importance in term of gene-wise maximum in-degree which decides the maximum number of regulatory genes including self-regulations that can be selected from a given method. Then, an evaluated gene score-based majority voting technique aggregates the selected gene lists from each method. In our experiments, the performance of the proposed ensemble approach was evaluated using gene expression datasets from three small-scale real gene networks. Our proposed model outperformed other state-of-the-art methods, producing high true positives, reducing false positives, and obtaining high Structural Accuracy, while maintaining model stability and efficiency. © 2022 IEEE.
Evaluating human-like explanations for robot actions in reinforcement learning scenarios
- Authors: Cruz, Francisco , Young, Charlotte , Dazeley, Richard , Vamplew, Peter
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022, Kyoto, Japan, 23-27 October 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Vol. 2022-October, p. 894-901
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- Description: Explainable artificial intelligence is a research field that tries to provide more transparency for autonomous intelligent systems. Explainability has been used, particularly in reinforcement learning and robotic scenarios, to better understand the robot decision-making process. Previous work, however, has been widely focused on providing technical explanations that can be better understood by AI practitioners than non-expert end-users. In this work, we make use of human-like explanations built from the probability of success to complete the goal that an autonomous robot shows after performing an action. These explanations are intended to be understood by people who have no or very little experience with artificial intelligence methods. This paper presents a user trial to study whether these explanations that focus on the probability an action has of succeeding in its goal constitute a suitable explanation for non-expert end-users. The results obtained show that non-expert participants rate robot explanations that focus on the probability of success higher and with less variance than technical explanations generated from Q-values, and also favor counterfactual explanations over standalone explanations. © 2022 IEEE.
Failure analysis of Slurry Pump assets in refinery for reduction of risks and costs
- Authors: Welandage Don , Chattopadhyay, Gopi , Kahandawa, Gayan , Kamruzzaman, Joarder , Zhang, L.
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022, Anand, India, 12-15 December 2022, 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022
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- Description: Assets fail due to design, manufacturing, installation, operations and maintenance, including ageing. Analysis of failures is needed for understanding the failure mechanism and identifying improvement opportunities to reduce risks and costs. Every year, the refinery spends a large amount of money on the maintenance of pumps and related accessories. There are unplanned maintenance and downtimes due to breakdowns. Reliability Centre Maintenance (RCM), Failure Mode and Effect Analysis (FMEA) and Residual life tracker, Equipment Management Strategy (EMS) were considered to create Preventive Maintenance (PM) activities and forecast the maintenance costs. However, budget overruns continued due to unplanned failures. This study analysed failures and identified gaps within the existing strategy for Washer and thickener underflow pumps. A review of maintenance activities was conducted along with review of design capabilities, failure modes and failure mechanisms and trends. Opportunities for improvements (OFI) were identified, and improvement actions were carried out to reduce risks and costs. © 2022 IEEE.
Feasibility study and design of an underground entry/access structure at an underground gold mine
- Authors: Carlisles, B. , Koroznikova, Larissa , Javidan, Fatemeh , Khandelwal, Manoj
- Date: 2022
- Type: Text , Conference paper
- Relation: 56th U.S. Rock Mechanics/Geomechanics Symposium, Santa Fe, USA, 26-29 June 2022, 56th U.S. Rock Mechanics/Geomechanics Symposium
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- Description: This paper investigates the viability of an increase in waste rock storage by backfilling the Falcon pit and extending the portal of the Fosterville gold mine, located in Bendigo, Australia. The structure will maintain the current access to the tunnel whilst developing a fillable void. Once completed the project will allow for a total increase of 900, 000 cubic metres of storage. Furthermore, a finite element study has been conducted to investigate the structural performance of a proposed design using corrugated steel sheets. Stresses and displacements are studied taking into account various design factors such as steel properties and geometry. Results demonstrate the location of critical stress values according to the proposed design. The selection of optimum steel geometry is also investigated with regards to the factor of safety. © 2022 ARMA, American Rock Mechanics Association.
Fuzzy-based operational resilience modelling
- Authors: Ur-Rehman, Attiq , Kamruzzuman, Joarder , Gondal, Iqbal , Jolfaei, Alireza
- Date: 2022
- Type: Text , Conference paper
- Relation: 9th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2022, Shenzhen, China, 13-16 October 2022, Proceedings - 2022 IEEE 9th International Conference on Data Science and Advanced Analytics, DSAA 2022
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- Description: Resilience is an increasingly important concept in current socio-economic landscapes. Due to the competitive global context and security attacks, the organisations are looking for realistic resilience assessments for operations of their digital networks. This study proposes a node Operational Resilience evaluation based on the fuzzy logic by assessing various cyber security dynamics; including node threat protection, avoiding degradation, attack identification and recovery vectors. Through extensive experiments and analysis, we reached to a better understanding of diverse relationships between cyber security factors for the evaluation of Operational Resilience. © 2022 IEEE.
Geometric design of the limaçon rotary compressor using bayesian optimization
- Authors: Lu, Kui , Sultan, Ibrahim , Phung, Truong
- Date: 2022
- Type: Text , Conference paper
- Relation: 3rd International Conference on Energy and Power, ICEP 2021, Chiang Mai, Thailand, 18-20 November 2021, AIP Conference Proceedings 2681 Vol. 2681
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- Description: In the design of positive displacement compressors, the mathematical relationship between design parameters and design objectives is usually impractical and costly to be extracted, making the optimization process becomes a 'black-box' problem. In the available literature, the Bayesian optimization method, compared to other optimization techniques, has been proven as an accurate and efficient method to solve the 'black-box' problem. However, the application of such a method in the design of the rotary compressor has not been discussed in published papers. Hence, the current study is intended to employ Bayesian optimization to geometric design a class of positive displacement compressors, which is known as the limaçon compressor. In this paper, the geometric characteristics of the limaçon compressor are presented, and a function, which incorporates volumetric and geometric aspects, is employed to evaluate the optimization process and to reveal the optimum design scenario as per design requirements. A case study is offered to prove the validity of the presented approach. © 2022 American Institute of Physics Inc.. All rights reserved.