936 research outputs found
Kaveh Akbar, 41st Annual ODU Literary Festival
No full textKaveh Akbar\u27s poems appear recently in The New Yorker, Poetry, The New York Times, The Nation, and elsewhere. His first book, Calling a Wolf a Wolf, is just out with Alice James in the US and Penguin in the UK. He is also the author of the chapbook Portrait of the Alcoholic. The recipient of a Pushcart Prize, a Ruth Lilly and Dorothy Sargent Fellowship from the Poetry Foundation, and the Lucille Medwick Memorial Award from the Poetry Society of America, Akbar was born in Tehran, Iran, and teaches in the MFA program at Purdue University and in the low-residency MFA programs at Randolph College
Emerging Strategies to Achieve Interfacial Solar Water Evaporation Rate Greater than 3 kg·m-2·h-1 under One Sun Irradiation
Full text linkSolar water evaporation is vital for addressing global water scarcity, particularly in regions with limited freshwater. Through the utilization of photothermal materials, solar water evaporation harnesses solar radiation to generate heat, which in turn accelerates the evaporation of water, producing clean drinking water. Subsequently, the vapor is condensed to produce fresh water, offering a sustainable solution to water scarcity. This research field has garnered immense scientific interest, with over six thousand publications. Reported solar absorber evaporation rates exceed 100 kg m−2 h−1 under one sun irradiation, far surpassing the theoretical limit of 1.47 kg m−2 h−1 achievable on two-dimensional absorber surfaces, assuming constant latent heat at 2444 J g−1. This review addresses this significant discrepancy in theoretical and practical values. A cut-off of 3 kg m−2 h−1 (under one sun irradiation) is considered to narrow focus, facilitating analysis of high-rate evaporators. Critical challenges and factors contributing to high evaporation rates are discussed, providing comprehensive insights into field advancements.Validerad;2024;Nivå 2;2024-07-03 (joosat);Funder: European Union (PE0000021); Kempe Foundation; Knut och Alice Wallenbergs Stiftelse; Swedish Foundations Consolidator Fellowship; Italian Ministry of University and Research; Full text license: CC BY 4.0;</p
PLACE OF MIR BAKHSHI IN THE ADMINISTRATION OF MUGHAL EMPEROR AKBAR
No full text Mir Bakhshi was basically the head of the army and the minister of defense, but when Akbar introduced the mansabdari system, civil officers and military officers were all appointed and all these mansabdars were declared subordinate to Mir Bakhshi. Mir Bakhshi's powers extended to both military and civil matters. This research is showing how the Mughal dynasty had reached to the highest level during the reign of Akbar, he strengthened the governmental affairs and succeeded in establishing a central government of his own over the whole of India
SPICE Modelling of commercially availabe 1200V, 30mΩ MOSFET at different Temperatures for Static Characteristics
No full textWhen compared to silicon, silicon carbide's (SiC) electro-thermal characteristics make it a strong contender for high voltage and high frequency applications. Since SiC power MOSFETs have been more widely available commercially just recently, there is an immediate need for precise simulation models to anticipate device behavior and facilitate circuit design. The silicon carbide (SiC) power MOSFET electro-thermal behavioral model (ETM) created by SPICE is presented in this study. The phenomena typical of static and dynamic behavior that depend on self-heating and junction temperature are covered in this model, which is based on the SPICE model. By using a single equation to describe MOSFET behavior spanning three distinct zones - weak, moderate, and strong inversion zones - the modified EKV model performs better than the reduced quadratic model. The model was simulated for different temperatures in comparison to DATASHEET for different characteristics. Accurate results are observed in comparison to the datasheet
Partial Discharge Separation by Using Pulses Cross-Correlation
No full textTo date, continuous monitoring of power grid
elements susceptible to aging processes is essential to increase
the reliability of these systems and avoid failures. In the field of
energy transmission, an index of the state of a cable insulation
system is partial discharge activity, which is influenced by the
presence of structural defects (e.g. voids within the material). In
High-Voltage-Direct-Current applications, given the dependence
of dielectric conductivity on temperature, this phenomenon is
also influenced by the load. Thus, partial discharge activity is
strongly related to the operating condition of the line and not
only by the aging of materials. Given the importance of partial
discharges monitoring, it is necessary to develop techniques
for analyzing them that allow the identification of different
types of discharges. The lack of a reference standard prompts
researchers to propose different approaches to achieve these
goals. This paper describes a comparison of two separation
algorithms both based on cross-correlation. Data used for
comparison have been obtained through a partial discharges
measurement, under DC voltage stress, on XLPE model cable.
The first algorithm evaluates the similarity among the pulses
and separates them into clusters following the acquisition order.
The second one, on the other hand, uses the correlation matrix
as input data, which must be calculated before running the
algorithm. The results show that both algorithms succeed in
identifying the same phenomena. The former with less accuracy
but employing less computation time than the latter. The latter,
on the other hand, provides higher accuracy but requires longer
computation time. The choice in using either algorithm can thus
be traced back to the desired accuracy/time ratio
Effect of Temperature on Main Partial Discharges Phenomena Under DC Voltage Stress
Full text linkThis work is aimed at characterizing the main
partial discharges phenomena under HVDC stress and with
the presence of thermal gradient. Specifically, the increase
in discharge activity without changes in applied voltage is
investigated. Even the supply and disconnection phases are
excluded from the analyzed acquisition range. In this way, any
variation in discharge activity can be attributed only to thermal
effects. A setup consisting of a pair of specimens connected in
series and supplied with a voltage of 20 kV DC has been used
for the tests. One specimen is defect-free and immersed in a
tank containing silicone oil. The other is designed to give rise
to certain discharge phenomenon. Three tests were carried out
using specimens for internal, surface, and corona discharges.
For each test, two acquisitions, lasting 30 minutes, have been
made. One with both specimens at room temperature and
another with the healthy specimen heated through a resistive
element in order to obtain a discrete thermal gradient. Thus,
a total of 6 acquisitions have been made and analyzed. The
results show that for all three specimens the discharge activity
undergoes a significant increase in the transition from the roomtemperature condition to the thermal gradient condition. The
increase in the amount of detected discharge is greater in tests
with corona and surface specimens. In general, an increase in
average discharge amplitude is also observed. The observed
changes can be attributed to a different distribution of the
applied voltage between the two specimens due to changes in
the conductivity of the defect-free specimen caused by heating.
This behavior is also found in variations in the electric field
profile in HVDC applications due to the presence of heat sources
that generate thermal gradients. For example, load currents for
cables
A Detailed Review of Partial Discharge Detection Methods for SiC Power Modules Under Square-Wave Voltage Excitation
Full text linkSilicon carbide (SiC) power modules are increasingly being used in high-voltage and high-frequency applications due to their superior electrical and thermal qualities. However, the issue of the partial discharge (PD) phenomenon raises serious reliability difficulties resulting in insulation failure, performance degradation, and potential device collapse. This paper provides a thorough assessment of the current PD detection strategies in SiC power modules. The issues provided by SiC devices’ distinct operational features, such as high switching frequencies and higher voltage stresses, which hinder PD detection and mitigation, are widely investigated. This review compares the effectiveness, benefits, and limitations of various detection methods, emphasizing the need for better strategies to ensure long-term reliability and performance. This study gives an in-depth overview of the numerous forms of PD phenomena that occur in power modules, including internal and surface discharges, as well as how they appear under various detection systems. It examines the performance of several methods for power module technologies such as SiC. To address these PD issues, this article proposes ways to improve reliability and detection accuracy
Prediction of Solar PV power using Deep Learning with Correlation-based Signal Synthesis
Full text linkEnhancement of the dispatching capacity and grid management efficiency requires knowledge of photovoltaic power generation beforehand. Intrinsically, photovoltaic power generation is highly volatile and irregular, which impedes its prediction accuracy. This paper proposes deep learning-based approaches and a pre-processing algorithm to handle these constraints. The proposed scheme employs Pearson's Correlation Coefficient to find the similarity between atmospheric variables and PV power generation. Based on high PCC values, top atmospheric variables and PV power generated time series data are passed through the Empirical Mode Decomposition (EMD) to simplify the complex data streams into Intrinsic Mode Functions (IMFs). Further, to streamline the prediction process, the proposed correlation-based signal synthesis (CBSS) algorithm finds combinations of these IMFs, which have a high correlation value between atmospheric variables and PV power data. Deep learning models of algorithms Long Short Term Memory (LSTM) and Nonlinear Autoregressive Network with Exogenous Inputs (NARX) network with the configurations of three networks, a single network, and the direct approach employed for the prediction of IMFs combinations. The LSTM network was analyzed under the Adaptive moment estimation (ADAM), Stochastic Gradient Descent with Momentum (SGDM), and Root Mean Square Propagation (RMSP) optimization. Extensive experimentation was evaluated using atmospheric data from the Climate, Energy, and Water Research Institute (CEWRI), NARC, Islamabad, Pakistan. RMSE, MAE, MAPE, and R 2 performance measures show promising prediction results for the LSTM under the configuration of three networks and ADAM optimization
Modified Hierarchical Clustering Algorithm for Partial Discharge Separation
Full text linkTo date, one of the main tools for evaluating the
reliability of an insulation system is the continuous monitoring
of those phenomena which, by interacting with the elements of
the system, can induce aging processes or failures. For power
grids, a signal that identifies possible aging or improper use
of the component is Partial Discharge (PD) activity. Generally,
the evaluation of the PD phenomenon is carried out through
a two-step procedure: measurement and data analysis. To
optimize the PD analysis process, increasingly sophisticated PD
separation/classification algorithms are needed. Especially for
the measurements carried out in HVDC systems for which the
absence of a phase reference makes more difficult to identify
the different types of discharge. The purpose of this article
is to investigate the possibility of optimizing the input data
to a hierarchical clustering algorithm in order to obtain a
subdivision of the dataset more faithful to the real behavior
of the phenomena. Specifically, the proposed approach is based
on the use of the cross-correlation matrix to carry out the
clustering operation. This matrix replaces the matrix of the
distances among the points distributed in the map used for
the representation of the data. Results show that with this
modification it is possible to separate phenomena that present
partially or completely overlapping patterns. Moreover, the
algorithm turns out to be automatic and does not require the
choice of references or thresholds to define the similarity among
pulses
Ghulam Mohammad: His Life & Work
No full textThe rule of Ghulam Mohammad as the Governor General of Pakistan (1951-55) is one of the controversial, authoritarian and undemocratic chapter of thePakistan politics. He was a man behind the gun which laid rest to twoimportant Ministries in East Pakistan and at center, and dissolved theConstituent Assembly which was to frame the future constitution of thecountry. It had already done the home work and was to present the finaldraft. He was a member of Constituent Assembly, Finance Minister whomQuaid-e-Azam called “My Financial Wizard”. He was a successful FinanceMinister, Master-planner and politically a man with undemocratic andunconstitutional mind. During his rule the seeds of military praetorian andbureaucratic rule were sown
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