Measured Performance Data Research Articles

Design and optimization of a combi boiler heat exchanger: A CFD-based approach

Heat exchangers are widely used in various fields, emphasizing the importance of efficiency and mass/dimensional improvements. Aluminum boiler heat exchangers play a crucial role in systems, where the natural gas-air fuel mixture is burned and heat transfer to water occurs. In such heat exchanger designs, the region where the air-gas mixture burns is referred to as the “combustion chamber,” and the thermal energy produced is transferred to the circulating water in the body.In this study, it was aimed to improve the heat transfer per unit surface by using novel pin–fin geometries in DAIKIN NDJ 24 kW aluminum cast boiler heat exchanger, thus reducing and lightening the dimensions of the combi heat exchanger for the same thermal performance. This approach targets cost reduction in production and downsizing of the boiler dimensions for more compact units. Cleanability limit was also established, and a unique symmetric droplet model was optimized utilizing a Computational Fluid Dynamics (CFD) based Response Surface Methodology (RSM) approach. Predictions of thermal performance through CFD simulations were subsequently validated experimentally using test bench available at DAIKIN’s facility in Sakarya, Türkiye. The results demonstrated a remarkable of 14% reduction in the overall weight, which was achieved by shortening the combi boiler height by 26 mm, while preserving the same efficiency levels. This research underscores the potential of the innovative pin geometry and optimized droplet model to enhance the efficiency and performance of the heat exchanger, with implications for cost savings and improved manufacturing processes. Also the effect of the new pin-fin geometry on the condensation performance was investigated as a multiphase phenomenon for the first time in the international literature. The results showed an excellent agreement between predicted and measured performance data.

Concrete Pavement Design Analysis Using AASHTOWare Pavement Mechanistic-Empirical Design Software

Local calibration of pavement performance models embedded in the AASHTOWare Pavement Mechanistic-Empirical Design (PMED) software may be needed to implement this design methodology. A recent survey showed that, despite local calibration, several state highway agencies in the U.S. are using the American Association of State Highway Transportation Officials (AASHTO) Guide for Design of Pavement Structures (1993 version) and the PMED software for comparative design of jointed plain concrete pavement (JPCP). This paper describes the recalibration process of the JPCP distress models in the PMED software and comparative designs obtained by the PMED software and 1993 AASHTO design guide. The results show that the calibration/recalibration process depends on the availability of measured performance data. Not all global coefficients must be changed in the calibration/recalibration process. The 1993 AASHTO design guide yielded higher JPCP slab thickness for projects with high truck traffic than the PMED software when no friction is assumed between the slab and a cementitious base. An assumption of full friction will have a discernible effect on the slab thickness obtained from PMED.

Automated Generation of Energy Profiles for Urban Simulations

Urban simulations play an important role on the way to a climate neutral society. To enable early assessment of different energy concepts for urban developments, energy profiles for different building types are needed. This work describes the development and use of a new engineering tool GenSim to quickly and reliably generate energy profiles for urban simulations and early building energy predictions. While GenSim is a standalone tool to create energy profiles for early design assessment, it was developed in the context of urban simulations to primarily support energy efficient urban developments within Germany. Energy engineers quickly embraced the tool due to its simplicity and comprehensible results. The development of the tool was recently switched to open source to enable its usage to a broader audience. In order to foster its development and use, a detailed testing framework has been established to ensure the quality of the results of the tool. The paper includes a detailed validation section to demonstrate the validity of the results compared to a detailed building energy simulation model and actual measured performance data.

Predicting future GB heat pump electricity demand

To meet net zero carbon targets by 2050s, countries with cold winters, such as Great Britain (GB), will turn to low carbon domestic heating systems such as electric heat pumps. In this paper, a statistical model is developed using measured performance data from over 550 heat pumps installed in GB homes in 2012. The model is used to predict the additional load on the GB electricity generation and distribution infrastructure for various current and future (2050) climates, dwelling energy efficiencies and heat pump deployment scenarios. For a cold year in the 2020s, a 100% uptake of heat pumps in the existing GB dwelling stock gave a peak electricity demand for the heat pumps of 78 GW and an annual electricity demand of 189 TWh. When added to the other, existing electricity demand, this represents an increase in the GB peak electricity demand in excess of 100% and an annual electricity demand increase of around 60%. Making reasonable assumptions about heat pumps’ future efficiency and use, and the future climate and dwelling stock fabric efficiency, and assuming 80% heat pump uptake and no load shifting, the peak heat pump electricity demand for a cold year in the 2050s halved to 37 GW. By shifting demand for water and space heating the 2020s cold year peak demand reduced by 15%. The work provides a more robust estimate of future GB heat pump electricity demands than any previously available. The predicted future ramp rates, peak and annual total electricity demands, are lower than predicted by previous analysts.

Flow Performance Analysis of Double-Chamber Gas–Liquid Transferring Device

Gas–liquid transportation is an efficient and economical transportation technology developed in recent years. It mainly uses some transportation equipment to simultaneously transport crude oil, associated natural gas, produced water, and so on for the purpose of reducing costs and energy consumption. In this paper, a double-chamber gas–liquid transferring device was selected as the research object. The VOF multiphase flow model of FLUENT software was used to simulate the gas–liquid two-phase flow performance under the design condition. The relationships between the two-phase flows, pressure, temperature, liquid level in the tank, outlet flow rate of the device, and time were calculated and analyzed. The results show that the operating cycle of the device can be divided into three processes, namely ‘suction-compression-discharge’, in which the cycle period formula is proposed as well. The pressures of gas and liquid in the device are basically the same, but the temperatures of the two phases are quite different in the compression process. In the compression process, the outlet valve is closed so that the outlet flow rate of the device is zero, and the gas compression process can be approximately treated as isothermal compression in engineering design. The comparison between the measured performance data in the oil field and the calculation results indicates that the calculation method in this paper is feasible for the performance prediction and optimization of the double-chamber gas–liquid transferring device.

Salary determination in professional football: empirical evidence from goalkeepers

ABSTRACT Research Question We consider how elite European football clubs use available and measurable performance data to value personnel by focussing on the goalkeeper labour market. We test the determinants of goalkeeper pay and discuss if football clubs effectively separate goalkeeper performances from outfield players. Research Methods Matching an exclusive salary dataset with rich performance measures, we estimate a Mincer-type salary model for a sample of 260 goalkeepers from five European football leagues (Premier League, Ligue 1, Bundesliga 1, Serie A and La Liga). Our dataset covers seven seasons from 2013/14 to 2019/20. Results and Findings We find that clubs use primitive defensive statistics to determine goalkeeper pay. Goalkeepers are paid based on co-production and team outcomes rather than individual workload. Also features of goalkeeper ball distribution positively affect salary - this indicates the importance of goalkeepers to initiating offensive moves. Implications Our evidence suggests that decision-makers within clubs are not optimally decoupling individual performance from team qualities. As such, clubs could improve how they value a key team member. Identifying the failure to use advanced statistics is especially important as forming contracts in this setting is costly.

Bottom-up uncertainty evaluation of complex measurements from correlated performance data: Determination of total Cr in yeast by ICP-MS after acid digestion

The objective interpretation of a measurement result requires knowing the associated uncertainty. The cost-effective collection of measurement performance data on the same day produces correlated values that can affect measurement uncertainty evaluation. This work describes a novel methodology for the bottom-up evaluation of measurements based on complex sample pretreatment and the instrumental quantification of the prepared sample applicable to correlated inputs. The numerical Kragten method is used to combine the uncertainty components shared in various analyte recovery determinations. The developed methodology was applied to the determination of total chromium in yeast samples by ICP-MS after microwave-assisted acid digestion. The developed analysis of yeast samples is fit for monitoring the contamination of this product since it is associated with a relative expanded uncertainty, U’, lower than 20%, ranging from 8.4% to 10.0% in determinations of Cr between 0.125 mg/kg and 305.5 mg/kg. Duplicate analyses are adequate for reference materials production (U′ < 7%).

Application and evaluation of a pattern-based building energy model calibration method using public building datasets

Building performance simulation has been adopted to support decision making in the building life cycle. An essential issue is to ensure a building energy simulation model can capture the reality and complexity of buildings and their systems in both the static characteristics and dynamic operations. Building energy model calibration is a technique that takes various types of measured performance data (e.g., energy use) and tunes key model parameters to match the simulated results with the actual measurements. This study performed an application and evaluation of an automated pattern-based calibration method on commercial building models that were generated based on characteristics of real buildings. A public building dataset that includes high-level building attributes (e.g., building type, vintage, total floor area, number of stories, zip code) of 111 buildings in San Francisco, California, USA, was used to generate building models in EnergyPlus. Monthly level energy use calibrations were then conducted by comparing building model results against the actual buildings’ monthly electricity and natural gas consumption. The results showed 57 out of 111 buildings were successfully calibrated against actual buildings, while the remaining buildings showed opportunities for future calibration improvements. Enhancements to the pattern-based model calibration method are identified to expand its use for: (1) central heating, ventilation and air conditioning (HVAC) systems with chillers, (2) space heating and hot water heating with electricity sources, (3) mixed-use building types, and (4) partially occupied buildings.

Monte Carlo bottom-up evaluation of the uncertainty of complex sample preparation: Elemental determination in sediments

Many chemical analyses involve a complex sample preparation, and some, based on an instrumental method of analysis such as spectrometric or chromatographic methods, are affected by matrix effects. The objective interpretation of the results of these analyses performed in the framework of a research or a conformity assessment requires quantifying the measurement uncertainty. This work presents a novel methodology for the bottom-up modelling of the performance of complex analytical operations, such as sample digestion or extraction, by the Monte Carlo simulation of their performance independently of the performance of the other analytical steps. The simulation of between-days precision of complex sample preparation and mean measurement error observed from the analysis of various reference materials and their combination with models of instrumental quantification performance allow the detailed modelling of the measurement uncertainty. The developed methodology adapts to the complex distribution of observed measurement performance data avoiding the under evaluation of the measurement uncertainty by assuming the normal distribution of systematic and random effects. The developed methodology was successfully applied to the determination of total or acid-extractable As (following OSPAR or EPA 3051A methods, respectively) in sediments where measurement trueness was assessed from the analysis of one Certified Reference Material and two spiked samples. The evaluated uncertainty is fit for environmental monitoring considering performance criteria defined for Quasimeme proficiency tests. The developed measurement models were successfully cross-validated by randomly extracting data from the validation set subsequently used to check the compatibility between estimated and reference values for 95% or 99% confidence level. The observed success rate of these assessments is compatible with the confidence level of the tests.

Construction, instrumentation and field performance of geogrid-reinforced unpaved roads

A research study involving full-scale unpaved road test sections was carried out to investigate the performance of unpaved roads reinforced with geogrids. Ten test sections were constructed with two different base course thicknesses. Three biaxial geogrids of different tensile stiffness and one geogrid with triangular aperture were evaluated. Geogrids were placed at the subgrade–base course interface. The sections were instrumented for measuring road response to traffic loading. Traffic loading was provided by a single-axle dump truck. Field measurements of rut depth and surface deformation were recorded at selected traffic intervals. An analysis of the measured performance data indicated that the geogrids effectively reduced surface rutting and improved the performance of unpaved thin base layers and the benefit became more pronounced when a stiffer geogrid was used. The results suggested reductions in the thickness of the base layer by using geogrids of up to 18%. The improvement by geogrids was shown to be less for increasing base layer thickness. In addition, the ability of the design procedure by Giroud and Han to predict rutting performance using the test section parameters as design inputs was assessed. The results indicated that the method underpredicted the required base thickness to support the applied traffic loads.

Performance Evaluation of Solar Photovoltaic Power Plants of Semi-Arid Region and Suggestions for Efficiency Improvement

This paper presents the performance evaluation of grid-connected solar PV power plants of 100kWp, 300kWp, and 2MW capacity in a semi-arid region with a hot-dry climate. The present study discusses on the energy generation and performance ratio (PR) of the solar power plants and identifies the reasons for the lower performance than expected. Their actual measured performance data is compared with the simulation results, and the gap in their performances are analyzed. Simulation has been performed using PVSYST software. A comparative study of three power plants presented in this paper show that amongst the three power plants of 100kW, 300kW, and 2MW SPV plants, the 100-kW plant has the highest actual performance ratio, 79.34%, than the other two plants. The actual performance ratio of the 300kW plant is 72.64%, and the 2MW SPV plant was 74.3%. The simulated performance ratios for 100kW p , 300kW p , and 2MW p plant are 83.72 %, 76.85%, and 80.9%, respectively. The analysis of the performance indicates that solar PV plants perform well in semi-arid regions, and the best performance is observed in the months of March, April and May. The performance can be further improved if, during designing and installation, care is taken about component efficiency, proper tilt angle and choice of site. While operating, frequent dust cleaning is required.

Quality Changes Among Primary Care Clinicians Participating in the Transforming Clinical Practice Initiative.

The Transforming Clinical Practice Initiative (TCPI) was designed to provide technical assistance to clinicians and prepare practices to participate in value-based payment arrangements. In this longitudinal cohort study, we assessed whether clinician's participation in TCPI practice transformation networks (PTNs) was associated with changes in quality of care from 2016 to 2018. We extracted quarterly measure performance data from 2016 to 2018 on two NQF-endorsed measures, one for outcome (Controlling High Blood Pressure) and one for process (Use of Imaging Studies for Low Back Pain), from 1,981 primary care clinicians enrolled in the PRIME Registry. Clinicians participating in PTNs were identified and compared with their counterparts who did not participate in PTNs. We found that the performance of PTN clinicians on controlling high blood pressure and use of imaging studies for low back pain was equivalent to that of non-PTN clinicians during the first 3 years of the TCPI. Although PTNs provided assistance to help practices achieve their clinical outcomes, these findings suggest that the changes in quality of care, for the measures studied, among PTN clinicians in the first 3 years of the TCPI were attributable to temporal trends rather than participation in PTNs.

Measurement uncertainty evaluation from correlated validation data: Determination of elemental impurities in pharmaceutical products by ICP-MS

Pharmaceutical products as well as active pharmaceutical ingredients (APIs) are checked for levels of elemental contaminants to guarantee medicines administration will not involve the consumption of level of contaminants greater than their maximum admissible intake. However, the conformity decision is affected by the measurement uncertainty function of analytical steps performance, used standards quality and how measurement performance is assessed during method validation. When an ingredient is considered conform, since the measured concentration is lower than the maximum limit, the risk of a false acceptance depends on how close the measured concentration is from the limit and on the measurement uncertainty. The analytical methods used for pharmaceutical analysis should be validated by ICH and USP recommendations, in order to prove measurements are fit for purpose. The validation must also be economically feasible and have an acceptable duration. This work discusses how to evaluate the uncertainty of elemental analysis in pharmaceutical ingredients from data collected during the validation of the analytical method by following ICH guidelines and USP chapters. A top-down uncertainty evaluation based on results from the analysis of a model API intermediate, with the native analyte after spiking at three concentration levels, where analyses are performed by two analysts in two different days, is presented. The impact of the correlation of some uncertainty components of collected results on the uncertainty evaluation is discussed and considered in the calculations. The developed measurement model was checked by a cross-validation procedure where some validation data was randomly removed and used for an independent model control. The developed uncertainty evaluation methodology was successfully applied to the analysis of Pd in a model API intermediate by ICP-MS after a micro-wave assisted acid digestion, where the risk of a false acceptance of the pharmaceuticals is determined. The measurement performance data and used spreadsheet are made available as Supplementary Material.

Potential of I/O Aware Workflows in Climate and Weather

The efficient, convenient, and robust execution of data-driven workflows and enhanced data management are essential for productivity in scientific computing. In HPC, the concerns of storage and computing are traditionally separated and optimised independently from each other and the needs of the end-to-end user. However, in complex workflows, this is becoming problematic. These problems are particularly acute in climate and weather workflows, which as well as becoming increasingly complex and exploiting deep storage hierarchies, can involve multiple data centres. The key contributions of this paper are: 1) A sketch of a vision for an integrated data-driven approach, with a discussion of the associated challenges and implications, and 2) An architecture and roadmap consistent with this vision that would allow a seamless integration into current climate and weather workflows as it utilises versions of existing tools (ESDM, Cylc, XIOS, and DDN’s IME). The vision proposed here is built on the belief that workflows composed of data, computing, and communication-intensive tasks should drive interfaces and hardware configurations to better support the programming models. When delivered, this work will increase the opportunity for smarter scheduling of computing by considering storage in heterogeneous storage systems. We illustrate the performance-impact on an example workload using a model built on measured performance data using ESDM at DKRZ.

Vision Algorithms for Sensing Soft Robots

The aim of this paper is the presentation and verification of computer vision algorithms in order to measure the geometric parameters of soft robots. The materials from which soft robots are made from possess large deformations. Embedded sensors or visual processing algorithms are often used to obtain measurement performance data from these robots. Integration of embedded sensors with soft robots can be cumbersome and expensive, also limiting the performance of a soft actuator. In this paper, implemented visual processing algorithms (thresholding, SAD, SSD and ZNCC) to measure performance data such as angle of motion, degree of bending, radius of curvature in real-time implemented with OpenCV libraries and Webcam is described. Soft RGB colour markers were also produced and firmly glued into the body of the soft robot with no hindrance to movement. Some concepts of visual processing applied include colour tracking, template matching and camera calibration. The execution of vision based motion control to a variety of soft actuators such as bending and wedge-shaped soft actuators was described.

Aerodynamic Thermodynamic Modeling and Simulation of Turbofan Engine

The mathematical model of turbofan engine is established and simulation calculation is carried out in this paper. An engine component model is established by means of the gas flow path of the engine. Then, according to the common working conditions, common working equations are established and the N+1 residual method is used to solve the nonlinear equations. The general model of an engine is established based on the design point parameters, and the specific performance parameters of the intermediate state are calculated under standard atmospheric conditions. The simulation results are compared with the measured performance data of the engine, which shows that: there are errors between the calculated value of the model and the measured value of the engine. The maximum error is 2.85%, which meets the requirement of model error less than 3% in general engineering.

Experimental and Numerical Results on the Performance of a Heat Pump

A 21 kW ground source heat pump (GSHP) operating since 2013 in Alaska is described in this paper. Six years of successful operation in an extreme climate and measured performance data from 2013 to 2017 prove the viability of heat pumps for extreme cold regions. Summary of performance evaluation data such as monthly electric energy use and cost, savings of the heat pump system compared to the cost of heating oil, energy extracted from the ground, heat delivered to building are tabulated by months. The coefficient of performance (COP) of the heat pump is calculated from the experimental data, which show the COP to vary from a maximum value of 4.15 to a minimum value of 2.34 depending on the heating load of the month and the ground temperature. Cost comparison shows savings by heat pump over regular heating oil boilers of 80% efficiency. In cold regions it is of concern that GSHP can create frozen ground or permafrost around the ground heat exchanger coil by extracting too much heat from the ground. A finite element heat conduction simulation performed over the ground heat exchanger coil spanning over a 30-year period shows that small volumes of frozen ground form around the coil each season, but they melt away during the summer by the recharge of heat from the solar heat gain. The mechanical system of the heat pump, sensors for measurements and cost of the system components are presented, which would be valuable to designers implementing heat pumps in various locations of the world.

Monitored performance of the first energy+ autonomous building in Dubai

This work presents the measured performance data related to the very-first Energy+ building in Dubai certified by the Passive House Institute. The building is a two-floor office structure, with 550 m2 total surface, designed under the guide and the scientific supervision of a Bergamo University research group, jointly to the Mohammed Bin Rashid Space Centre (MBRSC). The goal of the project was to assure a high level of internal comfort all over the year by using only solar energy. The building architecture has been designed to minimize the cooling load and the energy demand. The energy system is based on a 40 kWp PV field coupled with a 48 kWh electric storage and a high-efficiency chiller (reversible heat pump). Transient simulations by Trnsys code have been carried out to optimize both the thermal envelope and the energy plants so to make the building energy-autonomous 24/7. The numerical predictions of the energy performance (including cooling load, PV production and power consumption for chiller, lighting and appliances) are compared to the real data measured by a sophisticated monitoring system, including sensors located in the roof, in the external walls and in the energy systems. The field measurements confirm that the model predictions were accurate both in terms of peak and annual values. The small variations between prediction and real data show that both thermal envelope and PV field perform better than expected.This building is a pioneering pilot-project: the goal was to show that new sustainable construction standards using only solar energy are possible in the United Arab Emirates (UAE) and that this is a viable solution to reduce the carbon footprint in all the Gulf region. The strategic importance of an accurate modeling activity leading to an optimal design has been proved. The monitored data under real operating conditions have confirmed that the expected targets in terms of energy savings and carbon footprint reduction have been successfully achieved.

A novel shallow bore ground heat exchanger for ground source heat pump applications—Model development and validation

A novel ground heat exchanger design, the Underground Thermal Battery (UTB), was proposed as a low-cost alternative to the conventional vertical bore ground heat exchanger (VBGHE) for the application of ground source heat pumps (GSHPs). The UTB is designed to be installed in a shallow borehole (less than 6 m deep) and thus could cost much less than the conventional VBGHE, which usually is installed in vertical bores 60 m deep. By utilizing natural convection of water and phase change materials, the UTB tempers its temperature change in response to thermal loads, which helps improve the efficiency of GSHPs. A one-dimensional (1D) model of the UTB has been developed and validated with the measured performance data of a small-scale UTB, as well as the simulation results of a more detailed three dimensional (3D) numerical model, which accounts for both heat transfer and fluid dynamics in the UTB. This 1D model is computationally much more efficient than the 3D model and thus can simulate the annual performance of the UTB with acceptable computation time. The 1D model has been used to evaluate the performance of the UTB so that it can be compared with the conventional VBGHE.

Measured Performance of a Mixed-Use Commercial-Building Ground Source Heat Pump System in Sweden

When the new student center at Stockholm University in Sweden was completed in the fall of 2013 it was thoroughly instrumented. The 6300 m2 four-story building with offices, a restaurant, study lounges, and meeting rooms was designed to be energy efficient with a planned total energy use of 25 kWh/m2/year. Space heating and hot water are provided by a ground source heat pump (GSHP) system consisting of five 40 kW off-the-shelf water-to-water heat pumps connected to 20 boreholes in hard rock, drilled to a depth of 200 m. Space cooling is provided by direct cooling from the boreholes. This paper uses measured performance data from Studenthuset to calculate the actual thermal performance of the GSHP system during one of its early years of operation. Monthly system coefficients-of-performance and coefficients-of-performance for both heating and cooling operation are presented. In the first months of operation, several problems were corrected, leading to improved performance. This paper provides long-term measured system performance data from a recently installed GSHP system, shows how the various system components affect the performance, presents an uncertainty analysis, and describes how some unanticipated consequences of the design may be ameliorated. Seasonal performance factors (SPF) are evaluated based on the SEPEMO (“SEasonal PErformance factor and MOnitoring for heat pump systems”) boundary schema. For heating (“H”), SPFs of 3.7 ± 0.2 and 2.7 ± 0.13 were obtained for boundaries H2 and H3, respectively. For cooling (“C”), a C2 SPF of 27 ± 5 was obtained. Results are compared to measured performance data from 55 GSHP systems serving commercial buildings that are reported in the literature.