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13 results for “Energy engineering”
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility - Dataset
<p>This zip contains all input structures for paper the: Alchemical Free<br> Energy Estimators and Molecular Dynamics<br> Engines: Accuracy, Precision and Reproducibility</p> <p>Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney</p> <p>The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files</p> <p>The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q)</p> <p>There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop</p> <p>complex.pdb is structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file</p> <p>For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column.</p> <p>These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engiens that take AMBER input.</p>
EPSRC-funded Humanitarian Engineering and Energy for Displacement (HEED) datasets
<p>This repository contains raw datasets gathered under the EPSRC-funded Humanitarian Engineering and Energy for Displacement (HEED) research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities by creating an evidence base on the usage of seven different energy interventions, and provide recommendations for improved design of future energy interventions to better meet the needs of people. Below is a brief description of the interventions.</p> <ol> <li>Stove-use monitoring systems (July 2019 to October 2019) - Stove-use monitoring systems (SUMs) were deployed on clay stoves in Kigeme camp, Rwanda in July 2019. The aim of the study was to evaluate stove usage patterns by measuring temperature profiles within stove enclosure and on the surface of stoves. The SUMs consisted of 2 sensors - a thermocouple to measure temperature within the stove and a Si7021 sensor to measure temperature outside the stove, connected to an Arduino MKR GSM 1400 board. The data measured by the sensors was stored only if the change in values exceeded a set threshold for either of the readings. The SUMs were powered by a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh.<br> <br> The study was conducted in 2 phases. In phase 1 (02 July 2019 to 30 September 2019), data was collected from 15 SUMs and stored locally on SD cards as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. In phase 2 (02 October 2019 to 17 October 2019), data was collected from 9 SUMs and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board. The data from both phases of study is deposited here in SUM.zip. The cleaned dataset is available at <a href="https://doi.org/10.5281/zenodo.3946999">10.5281/zenodo.3946999</a>.<br> </li> <li>Mobile Lantern monitoring systems (July 2019 to December 2019) - Mobile lantern monitoring systems (LMSs) were deployed in Nyabiheke camp, Rwanda, in July 2019. The aim of the study was to evaluate lantern usage (static or mobile) and consumption (charge and discharge) patterns. The monitors consisted of a D.light S30 solar lantern fitted with an Arduino-based monitoring device. The most integral part of the device was the Arduino MKR GSM 1400 board connected to an ADXL345 inertial motion unit sensor. The ADXL was used to calculate step count of a user based on activity and freefall interrupts. Additionally, the voltage of lantern battery was measured using an in-house voltage monitor to understand the discharging and charging patterns. The step count and battery voltage data were stored only if a significant change in the step count was detected. The LMSs were powered through a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh.<br> <br> The study was conducted in 2 phases. In phase 1 (03 July 2019 to 30 September 2019), data was collected from 60 lanterns and stored locally on SD card as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. In phase 2 (09 October 2019 to 18 December 2019), the design of lantern monitors was modified to circumvent these issues. The data was collected from 54 lanterns data and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board. Additionally, an internal watchdog timer was used to reset the device in case of failures. While certain failures persisted, the data yield was considerably higher than phase 1 of the study. The data from both phases of study is deposited here in LMS.zip. The cleaned dataset is available at <a href="https://doi.org/10.5281/zenodo.4269809">10.5281/zenodo.4269809</a>.<br> </li> <li>Individual appliance monitors (December 2018 to January 2020) - Individual appliance monitors (IAMs) were deployed in Uttargaya settlement, Nepal, in December 2018. The IAMs were simple, cost-effective and unobtrusive devices to collect data on the energy usage of connected appliances. The aim of the study was to understand energy consumption and usage patterns of different household appliances in grid-connected sub-metered displaced communities. The monitoring system consisted of 2 types of devices – Energenie MiHome Smart Plugs MIHO005 (referred to as the IAM) to sense data relating to power and voltage drawn by the connected appliance, and gateway nodes to collect data from IAM. The main component of the gateway node was a Raspberry Pi fitted with an Energenie ENER314-RT (receiver-transmitter) add-on board to allow the Pi to communicate with the smart plugs. The data collected by the RPi gateway was stored locally in an SD card as well as sent to a remote server hosted at Coventry University.<br> <br> The study was conducted until January 2020. The raw data from the study is deposited here in IAM.zip. The cleaned dataset is available at <a href="https://doi.org/10.5281/zenodo.4271714">10.5281/zenodo.4271714</a>.<br> </li> <li>Footfall monitoring systems (December 2018 to January 2020) - Seven footfall monitoring systems (FMSs) were deployed alongside seven solar streetlights to measure step count of passers-by in the Uttargaya settlement, Nepal, in December 2018. The aim of the study was to understand the level of pedestrian movement in the area and evaluate the effect of streetlights on the level of activity. Therefore, the footfall monitors were deployed prior to commissioning of streetlights to gather baseline data. The footfall monitors consisted of a Raspberry Pi 3B, PiFace Real Time Clock and CAM008 70º night vision IR sensor to detect footfall. Upon detection, footfall count along with the direction of movement and the timestamp (measured from PiFace RTC) was stored onto an SD card and communicated to a remote server hosted at Coventry University. <br> <br> The study was conducted until January 2020. The raw data from the study is deposited here in FMS.zip. The cleaned dataset is available at <a href="https://doi.org/10.5281/zenodo.4271730">10.5281/zenodo.4271730</a>.<br> </li> <li>Standalone Solar System for a Community Hall (June 2019 to March 2021) - A standalone solar system was deployed in a Community Hall in Nyabiheke camp, Rwanda in June 2019. The aim of the study was to understand the energy consumption behavior within a set location, and create an evidence base on the value of energy and its benefits for growing cooperatives and learning communities. The standalone system comprised of 2kW of solar panels and 12.2 kWh GEL battery storage capacity. Additional components included a Victron 150/35 charge controller and a Venus GX and 48/3000 MultiPlus Inverter. The system powered four AC 2-pin sockets, a 30 W entrance light, and six 30 W indoor lights. Each light and socket were individually metered and controlled via a remote monitoring unit. This allowed for quotas, maximum draws and periods of use to be remotely controlled.<br> <br> The study was conducted until March 2021. The raw data from the study is deposited here in Hall.zip. The cleaned dataset until March 2020 is available at <a href="https://doi.org/10.5281/zenodo.3949776">10.5281/zenodo.3949776</a>.<br> </li> <li>PV-battery Microgrid (July 2019 to March 2021) - A PV-battery Microgrid was deployed in Kigeme camp, Rwanda in July 2019. The microgrid powered a playground and two nursery buildings. The aim of the study was to identify best practice in the construction, control and operation of a micro-grid as a shared resource, understand optimal design features for user interfaces that allow negotiation over energy priorities and needs and understand community priorities for energy in the context of early years education and the rate of growth in energy utilization. The micro-grid system comprised of a 2.5 kW of solar panels and 21.1 kWh GEL battery storage capacity. Additional components included a Victron 250/60 charge controller, Venus GX 48/1200 MultiPlus Inverter and BMV-700 series battery monitor. Each Nursery building had three classrooms (A, B and C) with separate entrances. Each classroom was fitted with an AC socket, five 10 Watt indoor lights and a 10 Watt outdoor entrance light. A spare socket was located in the first classroom of each nursery building (Classroom A). Two outdoor double sockets were installed at the playground, and fifteen 10 Watt lights were located in the roof structure. Three transmission line poles were fitted with three 10 Watt lights for safety and security purposes, which also enabled them to act as streetlights. Each light and socket was individually monitored and controlled via a programmable remote monitoring unit (RMU). Wireless AC smart meters were used to control and measure power consumption at the socket loads. These meters communicated with the RMU to receive commands and notified the RMU when a command had been received and to transmit usage data. Each light was connected to a CPE (customer-premises equipment) unit, with three lights per CPE, which communicated wirelessly with the RMU. The CPEs received information from the RMU on when to turn the lights on/off and set the brightness. The CPE also monitored the power consumption of the three lights. <br> <br> The study was conducted until March 2021. The raw data from the study is deposited here in Microgrid.zip. The cleaned dataset until March 2020 is available at <a href="https://doi.org/10.5281/zenodo.3949776">10.5281/zenodo.3949776</a>.<br> </li> <li>Standalone solar streetlights (Nepal - June 2019 to October 2020; Rwanda - July 2019 to March 2021) - Seven advanced streetlights were installed by HEED in Khalte, Nepal, in July 2019. Four advanced streetlights and eight normal solar streetlights have been installed in Gihembe, Rwanda, in July 2019. Each advanced streetlight consisted of a solar streetlight and an electrical socket box for excess energy use. The aim of the study was to pilot community co-designed solar streetlights with ground-level sockets to demonstrate alternative energy governance models using new technologies to build community resilience and capacity. The solar light comprised a 300 Watt solar panel, Victron charge controller, 2 kWh li-ion batteries, reprogrammable 60 W LED light, Victron Venus GX for data logging, Victron BMV 700 series battery monitor, ground-level sockets/USB ports and a footfall sensor (only in Nepal). A Victron Battery Protect and remote relay on the Venus GX is used to control access to the secondary load to ensure that there is always sufficient energy to power the light. <br> <br> The study was conducted until October 2020 in Nepal and March 2021 in Rwanda. The raw data from the study is deposited here in SL.zip. The cleaned dataset until March 2020 is available at <a href="https://doi.org/10.5281/zenodo.3947992">10.5281/zenodo.3947992</a>.</li> </ol>
Protein engineering using variational free energy approximation
<p>Data generated by PREVENT model and used in manuscript "Protein engineering using variational free energy approximation". Contains raw input data, R scripts and Jupyter Notebooks to process data and output figures used in the main text and supplementary materials of the manuscripts.</p>
Achieving Energy Efficiency with a Software Product Line Engineering Approach
<p>This is a Live PhD. Thesis Presentation; Also playable at:</p><p><a href="https://youtu.be/yaYEoj4S3pc">https://youtu.be/yaYEoj4S3pc</a></p><p>Please access and cite the published PhD. Thesis book: <a href="https://doi.org/10.5281/zenodo.10007921 ">https://doi.org/10.5281/zenodo.10007921 </a></p><ul><li><strong>Author</strong>: Daniel-Jesus Munoz</li><li><strong>Directors</strong>: Lidia Fuentes and Monica Pinto.</li></ul><p>CAOSD group, Universidad de Málaga, Andalucía Tech, Spain </p><p>Post-defense presentation recorded at Universität Ulm in 2023.</p><p>Energy-aware software design can energy-aware software design can reduce total energy consumption by 30-90%. However, the different ways of measuring energy consumption in real time are very complex. Energy readings are provided as the total energy consumption in joules or the rate of energy consumption in watts. For battery-powered battery-powered devices, joules per task is a more interesting metric, while watts per task is more commonly used for battery-powered devices. per task is more used for devices directly connected to power. The usual approach to modelling and storing approach to modelling and storing power consumption readings is to describe them as a characteristic of individual components, such as monetary cost. individual components, such as the monetary cost of a hardware component. However, the energy consumption values have many interactions between components, which makes it difficult to describe them with individual, static energy values. This makes it difficult to describe them in terms of individual, static energy values. Instead, we can store and energy information can be stored and populated in collaborative databases. The IEA and Datarade offer free databases with energy consumption data. free databases with energy consumption data for energy efficiency and sustainability analysis. Without However, the databases are not scalable for highly configurable systems because of the curse of the dimension. Our work focuses on Industry 4.0, specifically on Cyber-Physical Systems (acronym CPS), which are characterised by their high configurability and adaptability, presenting a large number of alternatives and a colossal number of alternatives and a colossal number of different systems in operation. This is known as the This is known as the search/solution space, the size of which is the set of all possible points that satisfy an optimisation problem. optimisation problem. Partially known solution spaces are a common problem in many fields, such as computer engineering, machine learning, artificial intelligence and goal-oriented optimisation. engineering, machine learning, artificial intelligence and goal-oriented optimisation. The Constraint Satisfaction Problems (CSP) are mathematical problems defined as a set of objects whose state must satisfy a set of constraints. set of objects whose state must satisfy a set of constraints. Variability Models (acronym VMs) are tree-like structures used to represent the commonalities and differences of a CPS. Numerical Features (NFs) can be used in VMs to represent quantitative properties of the system, but they can be used to represent quantitative properties of the system, but most tools do not support NFs. In addition, NFs increase the size of the VM, NFs increase the size of the solution space by multiplying it by its domain size, which makes large solution spaces colossal. large solution spaces into colossal ones. Quality Models (QMs) are tree structures that are used to determine which Quality Attributes (QAs) such as energy efficiency are to be taken into account when evaluating a project. which Quality Attributes (QAs) such as energy efficiency are to be taken into account when evaluating a system. system. ISO/IEC 25010 is the most popular QM formalisation, which groups QAs into eight different types. The Automated reasoning is the automation of formal logical reasoning to compute different types of information about system models. Examples are providing a VM or QM to a reasoning tool, and calculating the size of the reasoning tool, and calculating the size of the solution space, checking the satisfiability of the model, or generating only optimal systems based on objective functions. only optimal systems based on objective functions based on one or more QAs. This thesis aims to find a native modelling and reasoning approach for a unified Quality and Variability Model (QVM). Variability and Quality Model (QVM). The aim is to develop an approach that supports modelling and reasoning for the reasoning oriented optimisation of numerical characteristics, an algebraic framework for unified QVMs, an online eco-assistant for optimising a user-constrained solution space measured for quality, and an algorithm and an online quality, and an algorithm and a web tool for learning the influences of energy and characteristics of user-constrained, domain-unknown and partially measured solution spaces.</p>
Engineering the Compositional Architecture of Core-Shell Upconverting Lanthanide-Doped Nanoparticles for Optimal Luminescent Donor in Resonance Energy Transfer: The Effects of Energy Migration and Storage
<p>Förster Resonance Energy Transfer (FRET) between single molecule donor (D) and acceptor (A) is well understood from fundamental perspective and is widely applied in biology, biotechnology, medical diagnostics and bio-imaging. However, the reliability of molecular FRET measurements can be affected by numerous artefacts which eventually hamper quantitative and reliable analysis, mostly due to issues with the donor and acceptor molecules. Lanthanide doped upconverting nanoparticles (UCNPs) have demonstrated their suitability as alternative donor species. Nevertheless, while they solved most disadvantageous features of organic donor molecules, such as photo-bleaching, spectral cross-excitation and emission bleed-through, the fundamental understanding and practical realizations of bio-assays with UCNP donors remain challenging. Among others, the actual donor ions in individual donor UCNPs are the numerous activator ions randomly distributed in the nanoparticle at various distances to acceptors anchored on the nanoparticle surface. Further, the power dependent, complex energy transfer upconversion and energy migration between sensitizing and activating lanthanide ions within UCNPs complicate the decay based analysis of <strong><em>D</em></strong>-<strong><em>A</em></strong> interaction. In this work, the assessment of designed virtual core-shell nanoparticle (VNP) models led us to the new designs of UCNPs, such as …@Er, Yb@Er, Yb@YbEr, which were experimentally evaluated as donor nanoparticles and compared to the simulations. Moreover, the specific properties of lanthanide-based upconversion motivated us to analyze not only steady-state luminescence and luminescence decay responses of both the UNCP donor and the sensitized acceptor, but also the effects of their luminescence rise kinetics upon RET was discussed in newly proposed disparity measurements. The presented studies help to understand the role of energy-transfer and energy migration between lanthanide ion dopants (due to their concentration and spatial distribution) and how the architecture of core-shell UCNPs affects their performance as FRET donors to organic acceptor dyes.</p>
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility
<p>This zip contains all input structures for paper the: Alchemical Free<br> Energy Estimators and Molecular Dynamics<br> Engines: Accuracy, Precision and Reproducibility</p> <p>Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney</p> <p>The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files</p> <p>The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q)</p> <p>There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop</p> <p>complex.pdb is structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file</p> <p>For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column.</p> <p>These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engiens that take AMBER input.</p>
Dataset for article "Prediction of thermal shock induced cracking in multi-material ceramics using a stress-energy criterion" published in Engineering Fracture Mechanics
<p>Dataset contains graphical outputs of the numerical analysis performed using Finite element method in finite elements software Ansys Mechanical. It contains also photoes of the tested specimens. Further, material data used for the numerical analysis and measured by authors are included in the csv file and all necessary input codes for the FE system Ansys creating data for graphs in the publication are provided in the subfolder "Models-Ansys" within "Data" directory.</p> <p> </p>
Double-Fourier engineering of Josephson energy-phase relationships applied to diodes
<p>Code used to produce the numerical results presented in "Double-Fourier engineering of Josephson energy-phase relationships applied to diodes" manuscript.</p>
Additional material for the Wind Energy manuscript "An engineering approach for the estimation of slewing bearing stiffness in Wind Turbine Generators"
<p>This documment compiles the additional material for the manuscript “An engineering approach for the estimation of slewing bearing stiffness in Wind Turbine Generators”. The document shows the results for all the considered design points, comparing the the proposed approach with the Finite Element model.</p>
The influence coefficients used in Wind Energy Science paper "A computationally efficient engineering aerodynamic model for swept wind turbine blades"
<p>The influence coefficients for the convective correction with full double-precision floating-point accuracy. This is the supplement for the research article: "A computationally efficient engineering aerodynamic model for swept wind turbine blades", submitted to Wind Energy Science journal.</p> <p>Code language: Fortran</p>
A prototyping software engineering approach for designing and implementing model-based cloud mobile application for rationalized energy consumption
<p>The dataset used in this study comprises four files containing household consumers' energy consumption records. These records are collected at hourly intervals, providing detailed information on the energy usage patterns of the households. The dataset serves as a valuable resource for analyzing energy consumption trends, developing energy management strategies, and exploring the potential for energy efficiency improvements in residential settings.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility - Dataset
<p>This zip contains all input structures for paper the: Alchemical Free<br> Energy Estimators and Molecular Dynamics<br> Engines: Accuracy, Precision and Reproducibility</p> <p>Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney</p> <p>The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files</p> <p>The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q)</p> <p>There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop</p> <p>complex.pdb is structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file</p> <p>For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column.</p> <p>These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engines that take AMBER input.</p>
Formaldehyde as source of free-energy during growth of engineered Saccharomyces cerevisiae on glucose
GEO Series GSE8902. Saccharomyces cerevisiae. 8 samples. Type: Expression profiling by array.
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International Brain Laboratory public data
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OpenNeuro
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