scholarly journals Selection of Optimal Magnets for Traction Motors to Prevent Demagnetization

Machines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 124
Author(s):  
Dantam Rao ◽  
Madhan Bagianathan
Keyword(s):  
Flux Density ◽  
Electric Vehicles ◽  
Parallel Line ◽  
Low Grade ◽  
Lower Grade ◽  
Worst Case ◽  
Traction Motors ◽  
Knee Point ◽  
Point Of Intersection ◽  
Selection Of

Currently, permanent-magnet-type traction motors drive most electric vehicles. However, the potential demagnetization of magnets in these motors limits the performance of an electric vehicle. It is well known that during severe duty, the magnets are demagnetized if they operate beyond a ‘knee point’ in the B(H) curve. We show herein that the classic knee point definition can degrade a magnet by up to 4 grades. To prevent consequent excessive loss in performance, this paper defines the knee point k as the point of intersection of the B(H) curve and a parallel line that limits the reduction in its residual flux density to 1%. We show that operating above such a knee point will not be demagnetizing the magnets. It will also prevent a magnet from degenerating to a lower grade. The flux density at such a knee point, termed demag flux density, characterizes the onset of demagnetization. It rightly reflects the value of a magnet, so can be used as a basis to price the magnets. Including such knee points in the purchase specifications also helps avoid the penalty of getting the performance of a low-grade magnet out of a high-grade magnet. It also facilitates an accurate demagnetization analysis of traction motors in the worst-case conditions.

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

CASE STUDY ON CIRCUMSCRIBED GLIOMAS, THEIR CLINICOPATHOLOGICAL CORRELATION IN A TERTIARY CARE CENTER

2021 ◽  
pp. 42-45
Author(s):  
Esther Alffi Papang ◽  
K. Rama
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Tertiary Care ◽  
Biological Behavior ◽  
Low Grade ◽  
Lower Grade ◽  
Who Grade ◽  
Primary Tumors ◽  
Short Period ◽  
The Impact

The histogenesis and biological behavior of primary tumors of the central nervous system(CNS) are very diverse. The majority of present gliomas as benign, slow growing lesions classied as by the WHO classicati grade I or II (Low grade gliomas) on of CNS tumors. However, a signicant fraction of gliomas develop over a short period of time and progress rapidly and are therefore classied as WHO grade III or IV(High grade gliomas). Astrocytomas are primary central nervous system tumours that can develop in adults or in children. They arise from the Astrocytes. They can be divided into diffuse that generally have a higher grade and poorer prognosis and those that are localised that tend to be of a lower grade and have a better prognosis. In this study, we outline the basic histological spectrum and features, epidemiological aspects and grade of circumscribed gliomas (localised) or other Astrocytic tumours according to WHO classication . These are the Pilocytic Astrocytoma, Pilomyxoid Astrocytoma, Subependymal giant cell Astrocytoma, Pleomorphic xanthoastrocytoma and Anaplastic astrocytoma . The knowledge of these tumours are important as they are one of the commonest cause of mortality and morbidity in both the young and old, accounting for about 60% of the glial tumours. Therefore neuropathological diagnosis and tumour characteristics will therefore profoundly inuence the impact of treatment strategies.

scholarly journals Adaptive Robust Optimization-Based Optimal Operation of Microgrids Considering Uncertainties in Arrival and Departure Times of Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2646 ◽  
Author(s):  
Se-Hyeok Choi ◽  
Akhtar Hussain ◽  
Hak-Man Kim
Keyword(s):  
Robust Optimization ◽  
Electric Vehicles ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Market Price ◽  
Optimal Operation ◽  
Worst Case ◽  
Price Signals ◽  
Power Trading ◽  
The Impact

The optimal operation of microgrids is challenging due to the presence of various uncertain factors, i.e., renewable energy sources, loads, market price signals, and arrival and departure times of electric vehicles (EVs). In order to incorporate these uncertainties into the operation model of microgrids, an adaptive robust optimization-based operation method is proposed in this paper. In particular, the focus is on the uncertainties in arrival and departure times of EVs. The optimization problem is divided into inner and outer problems and is solved iteratively by introducing column and constraint cuts. The unit commitment status of dispatchable generators is determined in the outer problem. Then, the worst-case realizations of all the uncertain factors are determined in the inner problem. Based on the values of uncertain factors, the generation amount of dispatchable generators, the amount of power trading with the utility grid, and the charging/discharging amount of storage elements are determined. The performance of the proposed method is evaluated using three different cases, and sensitivity analysis is carried out by varying the number of EVs and the budget of uncertainty. The impact of the budget of uncertainty and number of EVs on the operation cost of the microgrid is also evaluated considering uncertainties in arrival and departure times of EVs.

scholarly journals Schistosomiasis: from established diagnostic assays to emerging micro/nanotechnology-based rapid field testing for clinical management and epidemiology

2019 ◽  
Vol 3 (1) ◽  
pp. 439-458 ◽  
Author(s):  
Maurice Mutro Nigo ◽  
Georgette Salieb-Beugelaar ◽  
Manuel Battegay ◽  
Peter Odermatt ◽  
Patrick Hunziker
Keyword(s):  
Point Of Care ◽  
Field Testing ◽  
Detection Methods ◽  
Low Grade ◽  
Analytical Strategy ◽  
Diagnostic Assays ◽  
And Control ◽  
Analytical Platforms ◽  
Selection Of

Schistosomiasis is a neglected invasive worm disease with a huge disease burden in developing countries, particularly in children, and is seen increasingly in non-endemic regions through transfer by travellers, expatriates, and refugees. Undetected and untreated infections may be responsible for the persistence of transmission. Rapid and accurate diagnosis is the key to treatment and control. So far, parasitological detection methods remain the cornerstone of Schistosoma infection diagnosis in endemic regions, but conventional tests have limited sensitivity, in particular in low-grade infection. Recent advances contribute to improved detection in clinical and field settings. The recent progress in micro- and nanotechnologies opens a road by enabling the design of new miniaturized point-of-care devices and analytical platforms, which can be used for the rapid detection of these infections. This review starts with an overview of currently available laboratory tests and their performance and then discusses emerging rapid and micro/nanotechnologies-based tools. The epidemiological and clinical setting of testing is then discussed as an important determinant for the selection of the best analytical strategy in patients suspected to suffer from Schistosoma infection. Finally, it discusses the potential role of advanced technologies in the setting near to disease eradication is examined.

scholarly journals Development and Validation of an Efficient MRI Radiomics Signature for Improving the Predictive Performance of 1p/19q Co-Deletion in Lower-Grade Gliomas

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5398
Author(s):  
Quang-Hien Kha ◽  
Viet-Huan Le ◽  
Truong Nguyen Khanh Hung ◽  
Nguyen Quoc Khanh Le
Keyword(s):  
Gold Standard ◽  
Binary Classification ◽  
Predictive Performance ◽  
Deletion Mutation ◽  
Gradient Boosting ◽  
Low Grade ◽  
Lower Grade ◽  
Chromosome 1P ◽  
Extreme Gradient Boosting ◽  
External Test

The prognosis and treatment plans for patients diagnosed with low-grade gliomas (LGGs) may significantly be improved if there is evidence of chromosome 1p/19q co-deletion mutation. Many studies proved that the codeletion status of 1p/19q enhances the sensitivity of the tumor to different types of therapeutics. However, the current clinical gold standard of detecting this chromosomal mutation remains invasive and poses implicit risks to patients. Radiomics features derived from medical images have been used as a new approach for non-invasive diagnosis and clinical decisions. This study proposed an eXtreme Gradient Boosting (XGBoost)-based model to predict the 1p/19q codeletion status in a binary classification task. We trained our model on the public database extracted from The Cancer Imaging Archive (TCIA), including 159 LGG patients with 1p/19q co-deletion mutation status. The XGBoost was the baseline algorithm, and we combined the SHapley Additive exPlanations (SHAP) analysis to select the seven most optimal radiomics features to build the final predictive model. Our final model achieved an accuracy of 87% and 82.8% on the training set and external test set, respectively. With seven wavelet radiomics features, our XGBoost-based model can identify the 1p/19q codeletion status in LGG-diagnosed patients for better management and address the drawbacks of invasive gold-standard tests in clinical practice.

CBIO-05. SOX2 CHROMATIN ARCHITECTURE AND ENHANCER ACTIVITY IN THE MAINTENANCE AND DEVELOPMENT OF NEURAL STEM CELLS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi28-vi28
Author(s):  
Devin Bready ◽  
Aram Modrek ◽  
Joshua Frenster ◽  
Jane Skok ◽  
Dimitris Placantonakis
Keyword(s):  
Stem Cells ◽  
Neural Stem Cells ◽  
Developmental Process ◽  
Embryonic Stem ◽  
Stem Cell Differentiation ◽  
Ctcf Binding ◽  
Low Grade ◽  
Lower Grade ◽  
Cell Of Origin ◽  
Putative Enhancer

Abstract Gain of function mutations in isocitrate dehydrogenase I (IDH1) result in the formation of the oncometabolite 2-hydroxyglutarate (2HG) in adult lower grade gliomas. To gain insight into mechanisms of gliomagenesis, our lab previously created a tractable human cellular model of low grade astrocytoma (LGA) using the putative cell-of-origin, human neural stem cells (NSCs), engineered to express mutant IDH1 and knockdown constructs against TP53 and ATRX, the two other genetic changes that accompany the IDH mutation in these tumors. We found that transcription factor (sex determining region Y)-box 2 SOX2, which is essential to NSC multipotency, the ability to differentiate to neuroglial lineages, behaves as a tumor suppressor during glioma initiation. In this context, we showed SOX2 is transcriptionally downregulated to impair NSC multipotency, thus locking NSCs in an undifferentiated state to initiate gliomagenesis. This downregulation occurs secondary to dynamic reorganization of the topologically associating domain (TAD) of SOX2 and the loss of contact with several genomic loci with histone modifications and chromatin accessibility suggestive of being enhancers. Here we show that those putative enhancers acquire enhancer-like features simultaneous to tje TAD organizing in a way that facilitates interaction with the SOX2 promoter during the process of pluripotent stem cell differentiation into neuroectodermal lineages, suggesting a developmental role. Preliminary data suggests that disruption of the SOX2 TAD by preventing binding of the genome organizer CTCF downregulates SOX2 expression in NSCs. Targeted silencing of several regions of a putative enhancer with CRISPRi also downregulates SOX2. In human embryonic stem cells (hESCs), interfering with these CTCF binding sites biases their differentiation away from the neuroectoderm. We are currently performing CRISPRi screen against all putative enhancer loci, teratoma formation assays on hESCs lacking relevant CTCF binding, and CRISPR mediated deletion of putative enhancers. Understanding this developmental process may reveal underlying vulnerabilities in LGA.

Application of Variational Geometry to the Analysis of Mechanical Tolerances

1989 ◽  
Author(s):  
P. M. Martino ◽  
G. A. Gabriele
Keyword(s):  
Mechanical Design ◽  
Worst Case Analysis ◽  
Prototype System ◽  
Tolerance Design ◽  
Worst Case ◽  
Geometric Tolerances ◽  
Solid Models ◽  
The Cost ◽  
Selection Of

Abstract The proper selection of tolerances is an important part of mechanical design that can have a significant impact on the cost and quality of the final product. Yet, despite their importance, current techniques for tolerance design are rather primitive and often based on experience and trial and error. Better tolerance design methods have been proposed but are seldom used because of the difficulty in formulating the necessary design equations for practical problems. In this paper we propose a technique for the automatic formulation of the design equations, or design functions, which is based on the use of solid models and variational geometry. A prototype system has been developed which can model conventional and statistical tolernaces, and a limited set of geometric tolerances. The prototype system is limited to the modeling of single parts, but can perform both a worst case analysis and a statistical analysis. Results on several simple parts with known characteristics are presented which demonstrate the accuracy of the system and the types of analysis it can perform. The paper concludes with a discussion of extensions to the prototype system to a broader range of geometry and the handling of assemblies.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

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