Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

World University root node

Department of Civil Engineering

Creative Construction Conference

Process Reengineering using Activity Theory and Domain Mapping Matrix Method in Delivering Public Construction Projects

A construction project is subjected to unique complexities that increase the probability of risk occurrence and adversely impact the achievement of the project objectives. Studies have shown that risks should be managed as early as possible in the project's life cycle, especially during the design phase. In doing so, key challenges arise from the fact that modern design process is inherently iterative in nature. Thus, the management of information exchange forms the basis for achieving the desired project objectives. Many tools and methods have been developed to manage the information exchange in design projects. However, Building Information Modeling (BIM) is one of the most widely used phenomena in the UAE's high-rise building projects. Though the adoption improves the overall project delivery, its application in the risk management of these projects is not widespread. Hence, this research aims to contribute in developing a risk management framework for the BIM-enabled design by identifying the key design phase related risks impacting the time of the projects. An interviews were conducted and the preliminary results identified the top 10 risks impact the time of the projects in the UAE. Further, the paper mapped the identified most significant risks against its possible BIM based solutions. © IEOM Society International.

Proceedings of the International Conference on Industrial Engineering and Operations Management

Identification of key risks impacting project completion time in UAE's building projects-Towards developing a BIM solution

Drastic industrial development has occurred in the pharmaceutical field for the last two decades for the sake of public health. The modern trend in the pharmaceutical industry is to detect and to quantify various analytes in complex matrixes at submicron concentrations. Thus, the chemical sensors and biosensors with improved performances for rapid, reliable, efficient, and cost-effective monitoring are highly required in the pharmaceutical industry. During the last decade, the incorporation of nanomaterials into chemical sensors and biosensors has boosted the advances in this area leading to relevant enhancements of their performance. The chemical sensors and biosensors embedded with nanomaterials can lead to an increase in their applicability in all stages of drug development such as purity of the drug, stereochemistry of the manufactured drug, and chiral separation and enantio-specific detection of the desired drug from the matrix. Nanomaterials coupled devices can also play an important role in preclinical and real-world analysis such as drug delivery study of the developed drugs, drug-to-drug interaction, metabolic studies, drug excretion analysis, and drug detection. This chapter will provide an overview of the role of carbon nanomaterials in the pharmaceutical industry to develop the biosensors for detection of various drugs by using electrochemical methods. © 2019 Elsevier Inc. All rights reserved.

Department of Chemistry

Nanoparticles in Pharmacotherapy

Nanomaterial-based electrochemical sensors in pharmaceutical applications

Computational electrodynamics (CED), the numerical solution of Maxwell's equations, plays an incredibly important role in several problems in science and engineering. High accuracy solutions are desired, and the discontinuous Galerkin (DG) method is one of the better ways of delivering high accuracy in numerical CED. Maxwell's equations have a pair of involution constraints for which mimetic schemes that globally satisfy the constraints at a discrete level are highly desirable. Balsara and Käppeli (2019) presented a von Neumann stability analysis of globally constraint-preserving DG schemes for CED up to fourth order. That paper was focused on developing the theory and documenting the superior dissipation and dispersion of DGTD schemes in media with constant permittivity and permeability. In this paper we present working DGTD schemes for CED that go up to fifth order of accuracy and analyze their performance when permittivity and permeability vary strongly in space. Our DGTD schemes achieve constraint preservation by collocating the electric displacement and magnetic induction as well as their higher order modes in the faces of the mesh. Our first finding is that at fourth and higher orders of accuracy, one has to evolve some zone-centered modes in addition to the face-centered modes. It is well-known that the limiting step in DG schemes causes a reduction of the optimal accuracy of the scheme; though the schemes still retain their formal order of accuracy with WENO-type limiters. In this paper, we document simulations where permittivity and permeability vary by almost an order of magnitude without requiring any limiting of the DG scheme. This very favorable second finding ensures that DGTD schemes retain optimal accuracy even in the presence of large spatial variations in permittivity and permeability. We also study the conservation of electromagnetic energy in these problems. Our third finding shows that the electromagnetic energy is conserved very well even when permittivity and permeability vary strongly in space; as long as the conductivity is zero. © 2019 Elsevier Inc.

Department of Mechanical Engineering

Journal of Computational Physics

Globally constraint-preserving FR/DG scheme for Maxwell's equations at all orders

Methane hydrate reservoirs are a potential alternative energy source identified in the recent years. This work develops a methodology to predict the gas production potential and hydrological transport properties of methane hydrate reservoirs using artificial neural network coupled with genetic algorithm. Hydrate dissociation due to depressurisation in a lab scale core recovered from field excavation is modelled as multi-component, multi-phase, chemically reacting, non-isothermal flow in porous medium with effective transport properties. A predictive surrogate model, mimicking the full scale model along with reservoir heterogeneity is then developed using a feed forward back-propagation artificial neural network trained using the Levenberg-Marquardt algorithm coupled with Bayesian regularization. Predictions of gas production potential obtained from the surrogate model are then compared with those obtained from the full numerical simulations as well as measurements reported in literature for prescribed values of hydrological transport properties. It is then interfaced with genetic algorithm to solve an inverse estimation problem involving prediction of reservoir hydrological properties namely porosity, intrinsic permeability and initial hydrate saturation from temporally varying gas production. The effect of uncertainties associated with measurement of gas production on the predicted hydrological properties is investigated numerically and suitable bounds are proposed based on a statistical analysis. © 2019 Elsevier Ltd

Thermal Science and Engineering Progress

Prediction of gas production potential and hydrological properties of a methane hydrate reservoir using ANN-GA based framework

We report the growth of a single crystal of PrIr3B2 by Czochralski pulling method and its structural and anisotropic magnetic properties. At room temperature, PrIr3B2 crystallizes in the hexagonal CeCo3B2-type (P6/mmm) structure. However, a change of crystal symmetry is indicated by a hysteretic transition observed in both the resistivity and heat capacity taking place at ≈ 280 K, which is similar to the observed transition from monoclinic (at room temperature) to hexagonal at 395 K previously reported in CeIr3B2 in literature. The jump in the heat capacity at the transition during cooling is nearly 400 J/mol K. The Curie-Weiss behavior of susceptibility conforms to a trivalent state of the Pr ions, which order antiferromagnetically or ferrimagnetically, as inferred from a relatively broad peak in the susceptibility centered around 10 K. The bulk magnetic transition is further corroborated by an anomaly in the heat capacity at low temperatures. Both the temperature dependence of magnetization, and the isothermal magnetization at 2 K reveal a highly anisotropic magnetic behavior in PrIr3B2 with c-axis [0001] as the hard direction of magnetization. The electrical resistivity shows normal metallic behavior down to TN, below which it shows an upturn suggesting the onset of superzone gap. © 2019 Author(s).

Department of Physics

Fulltext

AIP Advances

Investigation of structural and magnetic properties of PrIr3B2 single crystal

Energy management is a critical challenge in multi-core processors due to continuous technology scaling. Previous methods have mostly focused on the energy minimization of the processor cores. However, energy overhead of the off-chip voltage regulator (VR) has recently shown to be a non-trivial part of the total energy consumption and has been previously overlooked. In this paper, we propose an overall energy optimization method for the system that minimizes both per-core energy consumption and VR energy consumption using dynamic voltage frequency scaling (DVFS) and VR phase scaling by solving a comprehensive convex model. In order to improve the accuracy of the task latency model, a new task model considering both computation and memory access of the task is also developed. Furthermore, for better scalability and lower on-line overhead, we decompose our proposed convex method into two stages: an off-line stage and an on-line stage. During the off-line stage, we explore the convex model by assuming different numbers of active phases of the VR, various workload pressures and workload characteristics to collect the optimal frequency assignments under different scenarios. During the online stage, the specific frequency assignment for cores and optimal active phase number of the VR are selected and applied based on the actual workload pressure and its characteristics running on the cores. Experiments on real benchmarks show that when compared with state-of-the-art approaches, which are oblivious to VR overheads and exploit slack time to achieve energy minimization, our method can achieve a significant energy saving of up to 22.4% with negligible on-line overhead. IEEE

Department of Computer Science and Engineering

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Energy Minimization for Multi-core Platforms through DVFS and VR Phase Scaling With Comprehensive Convex Model

Aggressive technology scaling enabled very high integration density. Unfortunately, it also led to issues such as process variation, increased power density and consequently rising chip temperature resulting in accelerated device aging and poor lifetime reliability of different components in a manycore system. Moreover, thermal and power limitations let only a fraction of the chip function at full speed; the rest is the dark silicon. Most of the lifetime reliability enhancement solutions for the multi-/manycore systems in the literature are heuristic-based, while some use standard compute-intensive methods to solve the optimization problem making them not scale well with the manycore size. The heuristic-based solutions are formulated to search through the design space of a fine granularity making it huge, limiting their scalability. Also, these approaches do not account for the impact of different applications' execution behavior on the aging of the underlying cores, and their performance requirement distribution across the cores to their advantage. In this paper, we present our resource management strategies towards building scalable lifetime reliability enhancement solutions for dark silicon manycore systems. The first technique, Hierarchical Mapping approach (HiMap), maps a periodic workload employing a block-based hierarchical method that leverages dark cores for thermal mitigation. The second approach, LifeGuard, uses reinforcement learning to learn the applications' aging behavior, and is aware of the performance requirement pattern onto the core frequencies. It maps randomly arriving requests and is scalable to the number of applications and the size of a manycore. © 2019 IEEE.

2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design, IOLTS 2019

Towards Scalable Lifetime Reliability Management for Dark Silicon Manycore Systems

Flame jet impingement heat transfer is a well-established technique for obtaining high heat transfer rates in many domestic and industrial applications. The flame structure and the heat transfer characteristics of the impinging methane diffusion flame and partially premixed flame are experimentally investigated. The heat transfer characteristics of the impinging methane flame are determined using the minimization technique wherein the target surface is impinged by a methane flame from the bottom and is simultaneously cooled from the top by air jets of different Reynolds number. At steady state, one-dimensional energy balance across the impingement surface provides an over-determined system of equations which when solved using the minimization technique give the heat transfer coefficient of the flame jet, the reference temperature and the emissivity of the gas/flame beneath the impingement surface. The stagnation point heat transfer coefficient and reference temperature are found to be maximum for the case of flame just touching the impingement surface. The radial variation of the non-dimensional heat transfer coefficient and reference temperature is found to have a Gaussian profile. For low H/d's where the flame is impinging the target surface, the temperature at the stagnation zone is lower than in the radial position as the hot jet turns in the radial direction and impinges at a distance slightly away from the stagnation region. The separation of heat transfer components indicates that the heat transfer is convective dominant with radiation accounting to 10% of the total incident heat flux in the case of methane diffusion flame and 3.5% in the case of partially premixed flame. Re-radiation becomes a significant component of heat transfer, accounting to 25–30% of the incident heat flux, due to higher wall temperatures. The present study also investigates the effect of tube burner to plate spacing. © 2018 Elsevier Ltd