Reference Case Research Articles

Analysis of Li Auto's Marketing Strategy Based on Marketing Mix Theory

This paper analyzes Li Auto's marketing strategy through marketing mix theory, including links to its products and publicity concepts, a unique selection of additional electric vehicles, optimization of product quality and product series, an extensive direct sales network and major cities, the establishment of service centers in the region, etc. The paper suggests that Li Auto should strengthen advertising operations on the we-media platform and, at the same time, adhere to the combination of online and offline marketing methods, strengthen scientific and technological investigation and development, and continuously launch safer, more comfortable, and more convenient products according to the demands of users. In addition, the direct sales network should be expanded to improve the quality of after-sales service. The paper also makes an in-depth analysis of the market development trend of Li Auto and provides an important reference case for enterprise strategic choice. However, the paper has insufficient analysis of Li Auto's pricing strategy. In the future, Li Auto's price strategy will be discussed in more depth, including its pricing strategy, price adjustment strategy, and price matching with market demand, to evaluate its competitiveness and market performance more comprehensively.

ANN and CFD driven research on main performance characteristics of solar chimney power plants: Impact of chimney and collector angle

Solar energy systems operate directly connected to the sun. Solar chimney power plants are privileged systems that can provide power output even in cloudy weather and during hours when there is no sun. The design and sizing of this system, which researchers focused on after its first application in the 1980s, is very effective on its performance. In this study, the collector slope and chimney slope that give maximum power output for the Manzanares pilot plant are investigated with a 3D CFD model. Simulations made using the RNG k-e turbulence model and the DO (discrete ordinates) solar ray tracing algorithm provide results that are in high compatibility with experimental data and literature. It is understood that the system provides maximum power at 0.6° collector slope and 1.5° chimney divergence angle. It is seen that the system, which gives a power output of approximately 46 kW in the reference case, exceeds the power output by 4.5 times and reaches 216.853 kW in the design that includes the collector and chimney slope. The effects of the main elements of the system on the performance are also included by changing the collector radius and chimney height while preserving these inclination angles. More than the power output in the reference case, 49.233 kW, can be achieved with the inclined design, with a collector radius of 73.2 m and a chimney height of 155.68 m. Although the effect of increasing the chimney height on power output continues after 1.2 floors, its effect decreases. In the study, it is seen that increasing the chimney height and changing the collector radius provide a greater increase in power output. Furthermore, the scope extends to the incorporation of an Artificial Neural Network (ANN) model, presenting a novel approach to predicting SCPP system performance. The findings ascertain the utilisation of 9 neurons in the hidden layer of the ANN, demonstrating a precise alignment with the study data.

Robust Contact Computation in Non-Rigid Variation Simulation

Abstract Geometric variation is an inevitable element of any fabrication process. To secure the geometric quality of the assembled products, variation simulation is performed to control compliance with the set geometric requirements. In non-rigid variation simulation, contact modeling is used to avoid the virtual penetration of the components in the adjacent areas, enhancing the simulation accuracy. For frictionless contact models, numerical errors and convergence issues due to the deformation behavior of the interacting surfaces are still limiting the computational efficiency of solving this optimization problem. The optimization problem associated with a contact model is often large-scale, and in practice, fast and robust methods for achieving convergence are required. Previous implementations of contact modeling for non-rigid variation simulation have been prominently based on the Iterative or Penalty Methods. In this paper, a quadratic programming approach has been introduced, based on the Lagrangian multiplier method, for robust contact modeling in non-rigid variation simulation, and the performance of the proposed approach has been compared to the previously applied Iterative and Interior Point Method. The methods have been compared on three industrial reference cases, and the convergence and time-efficiency of each method are compared. The results show that robust optimization of the quadratic program associated with the contact model is highly dependent on the reduced stiffness matrix condition. Furthermore, it has been shown that robust and efficient contact modeling in non-rigid variation simulation is achievable through the proposed quadratic programming method.

Do We Over - Or Underestimate the Overall Cost Burden of Infectious Diseases in Aging Adults?

Background: Arithmetic average values about disease burden across aging adults are often used in the absence of having reliable access to real life data. Those values however assume group homogeneity in characteristics such as age, sex, disease incidence rates, or costs. The question arises about how much the overall outcome results, like total disease management costs, obtained under those homogeneity assumptions may deviate from real-world population data that may manifest non-homogeneous distributions. Without being able to have easily access to those real-world data and for getting a good approximation of the deviations in outcome results, a calculation method is proposed that should also indicate which factor may have a dominant influence on the cost difference between homogeneous and non-homogeneous results. The method should help focus the research for obtaining more accurate information from real-world data in subsequent steps that better estimate control gain of infectious diseases through new interventions. Methods: The method explores, as the outcome measure to assess, the relative deviation in overall infection management costs measured with homogeneity versus non-homogeneity design in the datasets of aging adults. Population modelling is used with an Extended Sensitivity Analysis Plan (ESAP) that simulates non-homogeneous, but realistic, approximates of age-specific distributional spread in demography, infectious disease, and its severity in people aged > 65 years old over a 1-year period in univariant and multivariant assessments. Disease management costs are adjusted for 3 infection severity levels with increased differences between them using multiplication factors up to 20 times the initial unit cost. Results: The assumed full homogenous dataset systematically overestimates up to 10% the overall disease management cost in aging adults when compared with a group simulated with non-homogeneous, but realistic distributions for age, infection, severity, and cost, mainly due to the difference in the demographic age composition. However, overall costs of a proposed homogeneous condition tend to underestimate the spending of non-homogeneous conditions when the reference case has a partially homogeneous setup instead of a full condition or when the demographic age-change in the non-homogeneous condition evolves towards age-demographic homogeneity (same number of people at each age with increasing age), a likely evolution in the coming 15 to 30 years. Conclusion: Assessing the current cost burden of infectious diseases in aging adults must consider exact age-composition of the demography, the type of infection spread with severity levels in function of age and their cost differences between severity levels to avoid unrealistic cost estimates when assuming unreal homogeneous group conditions that could currently overestimate the real costs.

Impact of Dynamic Wheel Loading on Flexible Pavement Responses for Non-Free Rolling Conditions

Since 2000, pavement design methodologies have transitioned from empirical to mechanistic-empirical procedures. However, the complexities of loading patterns, contact stress distribution, material characterization, vehicle maneuvering, and dynamic load amplification are still not fully considered, despite their significant effect on pavement performance. In this study, state-of-the-art numerical models were used to investigate the changes in critical pavement responses derived from the combined effect of roughness-induced dynamic loading and vehicle maneuvering. A decoupled vehicle–tire–pavement interaction approach composed of a random process to generate artificial road roughness profiles, a mechanical full truck model, and three-dimensional finite element tire and flexible pavement models allow the prediction of the impact of road roughness on vehicle dynamics. In addition, the study quantifies the effect of dynamic loading on contact stresses, and consequently, on pavement critical responses. Because of the expected increase in axle weight from truck electrification, overweight scenarios were also considered. Changes in load history and distribution of strain fields were assessed for two typical pavement structures (thin and thick). The combined effect of roughness-induced dynamic loading and vehicle maneuvering greatly altered the critical pavement responses associated with bottom-up fatigue cracking, near-surface cracking, and rutting. Under the most adverse conditions, the critical tensile strains at the bottom of the asphalt concrete increased up to 125%, the shear strain increased up to 100%, and the compressive strain escalated to 120% when compared with the reference cases. Higher temperatures exacerbated the impact of dynamic wheel loading and vehicle maneuvering.

Optimized thread-block arrangement in a GPU implementation of a linear solver for atmospheric chemistry mechanisms

Earth system models (ESM) demand significant hardware resources and energy consumption to solve atmospheric chemistry processes. Recent studies have shown improved performance from running these models on GPU accelerators. Nonetheless, there is room for improvement in exploiting even more GPU resources.This study proposes an optimized distribution of the chemical solver's computational load on the GPU, named Block-cells. Additionally, we evaluate different configurations for distributing the computational load in an NVIDIA GPU.We use the linear solver from the Chemistry Across Multiple Phases (CAMP) framework as our test bed. An intermediate-complexity chemical mechanism under typical atmospheric conditions is used. Results demonstrate a 35× speedup compared to the single-CPU thread reference case. Even using the full resources of the node (40 physical cores) on the reference case, the Block-cells version outperforms them by 50%. The Block-cells approach shows promise in alleviating the computational burden of chemical solvers on GPU architectures.

Post-combustion carbon capture process modeling, simulation, and assessment of synergistic effect of solvents

Post-combustion carbon capture appears to be a promising solution to reduce the emission of carbon dioxide (CO2) from power plants that generate electricity using either coal or natural gas. In addition, carbon capture process efficiency, capacity, and energy consumption have become challenging against the performance of the capture process. However, synergistic effect due to solvents blend has gained attention to reduce the process energy consumption and enhance process efficiency. In this study, blends of methyldiethanolamine (MDEA) and piperazine (PZ) at different concentrations were investigated using a validated post-combustion capture process model using Aspen HYSYS. Results were compared with 30 wt% monoethanolamine (MEA) as reference case. The effective process variables are concentration of solvents, the amount of water and solvent in the makeup section, viscosity of solvent, energy consumed in different process stages, and the amount of lean solvent flow rate. These variables were studied against fixed process variables using rate-based model. The study shows that using (43 wt% MDEA/7 wt% PZ) for post-combustion carbon capture needs 2.53 MJ/kgCO2 regeneration energy for 88.5% process efficiency compared to 4.003 MJ/kgco2 for 30 wt% MEA without the need for any process modifications. In addition, it was found that solvents synergistic effect contributes to resolving the drawbacks of post-combustion capture that will enable the high utilization of the process and contribution to reduce the consequences effect of climate change. Therefore, the study will help policymakers, industries and encourage researchers towards the large-scale commissioning of blended solvent -based post-combustion capture process.

Cost-effectiveness of avelumab first-line maintenance therapy for adult patients with locally advanced or metastatic urothelial carcinoma in France.

This study evaluated the cost-effectiveness of avelumab first-line (1L) maintenance therapy plus best supportive care (BSC) versus BSC alone for adults with locally advanced or metastatic urothelial carcinoma (la/mUC) that had not progressed following platinum-based chemotherapy in France. A three-state partitioned survival model was developed to assess the lifetime costs and effects of avelumab plus BSC versus BSC alone. Data from the phase 3 JAVELIN Bladder 100 trial (NCT02603432) were used to inform estimates of clinical and utility values considering a 10-year time horizon and a weekly cycle length. Cost data were estimated from a collective perspective and included treatment acquisition, administration, follow-up, adverse event-related hospitalization, transport, post-progression, and end-of-life costs. Health outcomes were measured in quality-adjusted life-years (QALYs) and life-years gained. Costs and clinical outcomes were discounted at 2.5% per annum. Incremental cost-effectiveness ratios (ICERs) were used to compare cost-effectiveness and willingness to pay in France. Uncertainty was assessed using a range of sensitivity analyses. Avelumab plus BSC was associated with a gain of 2.49 QALYs and total discounted costs of €136,917; BSC alone was associated with 1.82 QALYs and €39,751. Although avelumab plus BSC was associated with increased acquisition costs compared with BSC alone, offsets of -€20,424 and -€351 were observed for post-progression and end-of-life costs, respectively. The base case analysis ICER was €145,626/QALY. Sensitivity analyses were consistent with the reference case and showed that efficacy parameters (overall survival, time to treatment discontinuation), post-progression time on immunotherapy, and post-progression costs had the largest impact on the ICER. This analysis demonstrated that avelumab plus BSC is associated with a favorable cost-effectiveness profile for patients with la/mUC who are eligible for 1L maintenance therapy in France.

Assessing the tradeoffs in emissions, air quality and health benefits from excess power generation due to climate-related policies for the transportation sector

As the transportation sector continues to decarbonize through electrification, there is growing interest in quantifying potential tradeoffs in air pollution and health impacts due to potential excess emissions from the power sector. This study investigates air pollution and health impacts of policy-driven changes in the transportation sector and the associated power generation demand in the Northeast and Mid-Atlantic United States. Five illustrative scenarios were designed to capture the effects of different policies under the first mandatory market-based program to reduce greenhouse gases in the US power sector (Regional Greenhouse Gas Initiative—RGGI) and the Transportation and Climate Initiative (TCI). Considering future power generation with new renewable energy investments to meet demands from decarbonized transportation, the scenarios were framed using: 1. 2030 reference cases for both sectors and a hybrid TCI portfolio, 2. Departure from the reference cases defined by Pennsylvania included or not in RGGI, and 3. Power grid emissions estimated under clean energy standard (CES) policy and hybrid TCI portfolio. While the cross-sectoral policy effect on domain-wide concentrations is modest (max ΔPM2.5 ∼ 0.06 μg m3, ΔNO2 ∼ 0.3 ppbv, ΔO3 ∼ 0.15 ppbv), substantial increases in Ohio and West Virginia were attributed to Pennsylvania joining RGGI. With CES enacted and Pennsylvania in RGGI, significant reductions are seen in average concentrations (max ΔPM2.5 ∼ 1.2 μg m3, ΔNO2 ∼ 1.1 ppbv, ΔO3 ∼ 1.7 ppbv) except for Louisiana and Mississippi with corresponding disbenefits. When focusing exclusively on emissions reductions from transportation, the hybrid TCI portfolio had health benefits of 530 avoided adult deaths, and 46 000 avoided asthma exacerbations. With a ‘business as usual’ power grid, these benefits remain comparable and are mainly driven by NO2, followed by PM2.5 and O3. However, if Pennsylvania joins RGGI, total health benefits and spatial distribution change substantially, with a large portion of adverse health impacts moving from TCI states to Ohio and West Virginia. The overall monetized impact of a CES scenario can substantially exceed the estimated average range of 66–69 Billion US$, depending on the interaction with transportation decarbonization strategies and other drivers of exposure.

Sustainable astronomy: A comparative life cycle assessment of off-grid hybrid energy systems to supply large telescopes

PurposeSupplying off-grid facilities such as astronomical observatories with renewable energy–based systems (RES) instead of diesel generators can considerably reduce their environmental impact. However, RES require oversized capacities to counter intermittency and comply with reliability requirements, hence shifting the environmental impact from operation to construction phase. We assess whether 100% RES scenarios are favorable from an environmental point of view and discuss the trade-offs in systems with backup fossil generators versus 100% renewable ones.MethodsIn this comparative life cycle assessment (LCA), we study various RES supply systems to power a new telescope in the Atacama Desert, Chile. We compare six setups, including 100% RES scenarios, namely, photovoltaics (PV) with batteries and hydrogen energy storage; high-renewable scenarios, with fossil fuel power generation next to RES and storage; and a system combining PV with diesel generation. We base system sizing on a techno-economical optimization for the start of operation in 2030. Foreground data stem from life cycle inventories of RES components since 2015 and 2030 electricity mix assumptions of production countries. We assess environmental impact in the categories climate change, mineral resource depletion, and water use.Results and discussionWe find that 100% RES and high-renewable scenarios result in emissions of 0.077–0.115 kg CO2e/kWh supplied, compared to 0.917 kg CO2e/kWh in the reference case with solely diesel generation. One hundred percent RES scenarios have a lower CO2e impact than high-renewable scenarios. However, the latter lower the mineral resource depletion and water use by about 27% compared to 100% RES scenarios. Applying hybrid energy storage systems increases the water use impact while reducing the mineral resource depletion.ConclusionsNone of the six energy systems we compared was clearly the best in all environmental impacts considered. Trade-offs must be taken when choosing an energy system to supply the prospective off-grid telescope in Chile. We find high-renewable systems with some fossil generation as the better option regarding power reliability, mineral resource depletion, and water use, while inducing slightly higher greenhouse gas emissions than the 100% RES scenarios. As remote research facilities and off-grid settlements today are mainly supplied by fossil fuels, we expect to motivate more multifaceted decisions for implementing larger shares of RES for these areas. To advance the LCA community in the field of energy systems, we should strive to incorporate temporal and regional realities into our life cycle inventories. To ease the path for upcoming studies, we publish this work’s inventories as detailed activity level datasets.

Constitutions of the Chapter of Samogitian Cathedral: Letter, Spirit, Life

The aim of the paper is to examine implementation of the laws of the cathedral chapter of the diocese of Samogitia according to the acts of the general sessions of the chapter (for the period from 1613 to 1913). The corpus of the constitutions, or statutes of the chapter was created in 1561–62 by the famous mid-16th century Lithuanian lawyers, Canon Pedro Ruiz de Moros (Petrus Roysius) and Bishop Joannes Domanowski. Despite the fact that already in 1637 Bishop Georgius Tyszkiewicz added some new constitutions (published in the annex of the paper), and there were subsequent attempts to ‘modernize’ the old corpus of the constitutions in the late 18th – early 19th century, the Roysian statutes retained their validity and exceptional authority in the life of the Samogitian cathedral chapter as long as 1925 when the old statutes were fundamentally revised.The constitutions predominantly influenced decisions of the chapter via hearing and memory. Due to the limited copies of the text which had to be not too much multiplicated in order to preserve secrecy, majority of canons were aware of the contents of the constitutions from reading aloud (usually, in fragments than in extenso) during the general sessions of the chapter. Perhaps this could explain occasional cases of erroneous allusion to the text of the constitutions in the decisions of the chapter. In some other cases, aspiration to ground the decisions of the chapter with solid arguments could inspire canons to invoke hardly definable ‘spirit’ (mens) of the constitutions. However, usually the constitutions were quoted correctly; the cases of clear reference to specific articles of the constitutions found in the acts of the general sesssions of the chapter are listed and described in the final part of the paper.

Development of a fast-running method for prediction of blast propagation in partially confined spaces

In this contribution, a series of findings from Computational Fluid Dynamics (CFD) simulations of blast propagation within fully confined spaces are presented. These numerical works have been carried out as part of an ongoing in-house development towards a fast-running method to predict overpressures and impulses arising from detonations within the various configurations of carparks in Singapore. In land-scarce cities like Singapore, carparks are typically located within the same structural footprints and are integrated with other functions of the building to facilitate convenient access. Design of carparks are required to meet statutory provisions with regards to the layout, headroom clearance and safety. To this end, the present research study has adopted a three-stage approach. First, different representative configurations of carparks are determined by making reference to and rationalising based on the prevailing statutory provisions in Singapore. This is then followed by a series of parametric CFD simulations to obtain essential numerical data in order to characterise the blast propagation within the respective partially confined spaces. Finally, several regression models are employed to derive relationships between the critical parameters and the blast data, with the aim of achieving a fast-running predictive method. This paper seeks to provide detailed descriptions of the first and the second stages, as well as to present the comparisons of numerically converged solutions, which are obtained from preliminary CFD simulations using two mesh sizes, against semi-analytical solutions which are calculated based on guidance from UFC 3-340-02 for fully confined detonation as initial reference cases.

Development and validation of a Bayesian unfolding program using OpenBUGS open-source software for Bonner spheres neutron spectrometry

This study presents the development of a novel unfolding program based on a Bayesian method for Bonner spheres spectrometry. The program incorporates a priori information on the neutron spectrum, employing a linear superposition of three non-negative parametric functions: thermal-Maxwellian distribution, an intermediate region represented by a straight line in lethargy space (1/E behavior), and the Watt fission distribution for the fast region. The effectiveness of the developed program was validated through its application to two reference cases from the EURADOS 2018 exercise (LINAC and Skyshine), followed by its implementation in characterizing the neutron field around an OB26 neutron irradiator at the Secondary Standards Dosimetry Laboratory (SSDL) of the Nuclear Research Center of Algiers (CRNA), Algeria. While validation results for the LINAC case were promising, achieving comparable neutron spectrum shape and integral quantities to the reference, challenges were encountered with the Skyshine case. However, these challenges were partially addressed through sensitivity analysis, resulting in slightly improved outcomes compared to the previous participation and to the reference. Application of the program to characterize the neutron field around the OB26 irradiator yielded satisfactory results when compared to reference data. A two-step sensitivity analysis further enhanced the outcomes, initially substituting the Watt fission distribution with the evaporation distribution, thereby improving spectrum shape and integral quantities. Subsequently, utilizing the obtained neutron spectra as prior information for unfolding codes MAXED and GRAVEL ensured stability and agreement with reference data and preliminary results.

Household-scale digesters in Rwanda: Performance analysis and net-greenhouse gas effect

In view of climate change mitigation, the production of biogas through anaerobic digestion has emerged as a prominent renewable fuel source, also in developing countries. The implementation of household-scale digesters in these regions is instrumental in achieving the Sustainable Development Goal 7 of ensuring clean and affordable energy. However, a rigorous quantification of the biogas production and net-greenhouse gas effect of these household digesters, taking into account fuel use, biogas leakage and fertiliser types, is lacking. This study quantified both biogas production and net-greenhouse gas emissions, utilizing Rwanda as a reference region. Through a field survey, biogas measurements, and model simulations, the study revealed that a reference case featuring a fixed dome digester of 4 m3, fed with manure of on average 2 cows produces 0.38 m3 biogas.d−1 which meets 65% of the cooking need of an average family of 4 adults and 2 children. The addition of a toilet to the household-scale digester increased the daily biogas production by 16%. Conversely, the use of a bare soil floor in the cow shed results in a 28% reduction in biogas production, emphasizing the recommendation for a concrete floor. Net-greenhouse gas emissions from a household-scale digester, including an estimated 9% leak percentage, result in a reduction of 2.4 tCO2,eq.year−1 per household compared to wood-only cooking. Besides, using the digestate as a fertiliser further enhances the reduction to a total of 2.5 tCO2,eq.year−1. The main opportunities for minimizing emissions include optimizing temperature, manure flow and reducing leakages, which needs to be considered during design, operation, and policy formulation. In summary, household-scale digesters provide sustainable waste management, renewable energy, and significant greenhouse gas emission reduction, making them a promising technology for decentralized energy solutions in developing regions.

Energy efficiency of ecological buildings in Tunisia: Natural fiber composites and passive strategies impact

Improving the thermal insulation and energy efficiency of building envelopes is a major objective worldwide and has significantly developed in the recent years. This study aims to evaluate the impact of ecological additive and passive strategies on building energy efficiency. An experimental study was carried out to examine the effect of the incorporation of treated Alfa and Posidonia-Oceanica fibers on the thermal properties of cement and gypsum composite samples. The experimental results were then introduced in a numerical study using TRNSYS software to perform a comparison of the energy efficiency and thermal performance of three individual buildings; two ones constructed with our ecological materials and the third one with typical materials is considered as a reference case under the Tunisian climate. The obtained results indicate that the buildings built with Alfa fibers (BAF) and Posidonia-Oceanica fibers (BPOF) are economically effective since they allow a decrease of about 48.20% and 43.48% in heating, 45.71% and 42.77% in cooling, leading to a reduction in CO2 emission of 47.90% and 43.40%, respectively, in comparison with the reference case. The investigation also focuses on the improvement of the ecological building envelope by a storage wall integrated on the south front and shaded by solar movable overhangs during the summer season. The indoor climate results reveal that incorporating passive strategies into the building improves indoor air temperature and preserves a comfortable indoor relative humidity. Heating requirements decrease by 82.82% for BAF and by 79.76% for BPOF. The cooling requirements of the reference building are also reduced by 63.46% for BAF and 60.45% for BPOF by the use of natural night ventilation (4 ACH) and the appropriate shading for Trombe walls and windows. Consequently, the implementation of passive strategies on the ecological buildings led to a net reduction in CO2 emissions by up to 80.55% for BAF, compared to the reference case.

Energy saving and flexibility analysis of combined heat and power systems integrating heat-power decoupling technologies in renewable energy accommodation

World energy is undergoing a decarbonization transformation with the rapid growth of renewable energy. Combined heat and power, with its abundant stock and efficient characteristics, can support decarbonization. This study focuses on enhancing the energy saving and flexibility of combined heat and power systems decoupled by the vapor compression heat pump and electric boiler. The characteristics of the governing valves and the governing stage are confirmed as key factors influencing energy saving. A general modeling method is proposed to accurately determine the characteristics of the governing valves and the governing stage. The valve-point effect is obtained from the formation mechanism. With a reference case, applying the heat-power decoupling technologies results in a maximum reduction of power load of up to 70 MW, greatly enhancing the operation flexibility. The fuel saving per unit peak shaving ranges from 0.1355 kg·kWh−1 to 0.1382 kg·kWh−1 in the system decoupled by the electric boiler and from 0.2284 kg·kWh−1 to 0.2481 kg·kWh−1 in the system decoupled by the vapor compression heat pump. The maximal variation ranges of fuel saving per unit peak shaving, with and without the valve-point effect, are 0.0197 kg·kWh−1 and 0.0055 kg·kWh−1, respectively. After considering the valve-point effect, the range of fuel saving per unit peak shaving is tripled. Additionally, there are higher energy-saving regions near valve points. It is recommended to operate the decoupling systems under these working conditions, with governing valves opened at an appropriate opening degree. The energy-saving potential of these systems can be further exploited by accommodating the valve-point effect in the integration of renewable energy.

Numerical analysis of a mini wind tunnel and experimental investigation of the mini wind tunnel utilizing a portable, three-axis load/balance measurement system

Investigation of a portable three-axis load/balance measurement system in a mini wind tunnel is the main subject of study. Firstly, a mini wind tunnel is designed, numerically analyzed and constructed. Then, measurements of lift and drag forces on a selected airfoil are carried out using data from the measurement system located in the test area. Tri-axis load/balance measurement system developed has a total of three load cells, one for drag and two for lift. Sensor data acquisition codes are written using Ardunio and force measurement experiments are performed at various angles of attack on the NACA2412 airfoil at Reynolds number of 60000, for the maximum flow rate of 5200 m3/h through fan controller in the constructed mini wind tunnel. After completing the mesh independence test, numerical studies are conducted in ANSYS Fluent for the same range of angles of attack using three different turbulence models. Realizable k-ε turbulence model gives more realistic high stall angles of attack than other turbulence models and similar to experimental results. In addition to the current experimental study, four other literature studies in similar Reynolds number ranges are used as reference cases. A visual study of the flow around the airfoil is given as velocity contours in addition to the numerical comparisons. From the numerical and experimental results, it is concluded that the NACA2412 airfoil profile wings are more efficient for moderate to high Reynolds numbers and the constructed load/balance measurement system and mini wind tunnel are highly successful in terms of lift and drag measurements.

Towards Tests of an RFQ Cooler and Simulations

The cooling of secondary beams is important for accelerator-based nuclear physics. In the radiofrequency (RF) quadrupole cooler (RFQC), RF fields and ion-gas collisions may give a considerable increase or decrease of the beam transverse emittance and energy spread, depending on a delicate tuning of heating and cooling effects, dominated by the ion beam kinetic energy and the balance of collisions and confinement forces. An extra confinement may be added by a solenoid magnetic field, as in the RFQC prototype installed in the Eltrap machine. This provides a versatile test bench (distinct from a closed accelerator installation) for detailed studies of cooling dynamics and of several RFQC technical optimizations (for gas differential pumping and bias voltages). Modeling concepts and simulation results are summarized. The major RFQC parameters are reviewed, in particular for 133Cs+ collisions against He gas whose pressure pg ranges from 2 to 9 Pa in the reference case, with attention to the extraction, comparing triode/tetrode system, and to the bias voltages. Lower bias voltages request less pg , but provide less cooling of the energy spread.

EFFECT OF THE STRANDS FIXITY PROFILE SHAPE ON THE FLEXURAL BEHAVIOR OF STEEL BEAMS

This study concerns the effect of the external prestressing strand shape profile on the flexural behavior of steel beams. Seven steel beams that have the same cross-section are strengthened by external strands fixed by using Saddle Points of Deviation (Deviators). Based on two criteria, beams tested are divided into two categories whether external prestressing with fixity strands is present. The first group includes only one beam as a reference, while the second group deals with beams strengthened by two external strands. Six samples have been separated according to the eccentricity for external prestressing at a jacking stress of 815 MPa. During testing, it was discovered that the moment-curvature responses at the bottom and top flange region were stiffer than those in the reference, and the degree of hardening increases with eccentricity increasing. However, failure occurs with a slight warning as a result of insufficient ductility. Due to the presence of external prestressing, the ultimate moment capacity is enhanced by approximately 6.1%, 31.7%, 38.5%, 57.6%, 29.4%, and 80.2% as compared to the reference. Finally, the radius of curvature at the top flange region for strengthening samples has grown by approximately -16.7%, 8.0%, -26.9%, 21.5%, 17.5%, and 17.4% as compared to the reference case. In contrast, the percentage of the radius of curvature at the bottom flange region for strengthened samples dropped to 24,9%, 73.9%, 83.2%, 83.6%, 69.2%, and 89.0%, respectively, with an increase in the eccentricity position as compared to the reference.

Synchronous Diagnosis of Diabetic Retinopathy by a Handheld Retinal Camera, Artificial Intelligence, and Simultaneous Specialist Confirmation

PurposeDiabetic retinopathy (DR) is a leading cause of preventable blindness, particularly in underserved regions where access to ophthalmic care is limited. This study presents a proof of concept for utilizing a portable handheld retinal camera with an embedded artificial intelligence (AI) platform, complemented by a synchronous remote confirmation by retina specialists, for DR screening in an underserved rural area. DesignRetrospective cohort study Subjects1,115 individuals with diabetes. MethodsA retrospective analysis of a screening initiative conducted in four municipalities in Northeastern Brazil, targeting the diabetic population. A portable handheld retinal camera captured macula-centered and disc-centered images, which were analyzed by the AI system. Immediate push notifications were sent out to retina specialists upon the detection of significant abnormalities, enabling synchronous verification and confirmation, with on-site patient feedback within minutes. Referral criteria were established, and all referred patients underwent a complete ophthalmic work-up and subsequent treatment. Main outcome measuresProof-of-concept implementation success. ResultsOut of 2,052 invited individuals, 1,115 participated, with a mean age of 60.93 years and diabetes duration of 7.52 years, of whom 66.03% were women. The screening covered 2,222 eyes, revealing various retinal conditions. Referable eyes for DR were 11.84%, with an additional 13% for other conditions (diagnoses included various stages of DR, media opacity, nevus, drusen, enlarged cup-to-disc ratio, pigmentary changes, and other). AI performance for overall detection of referable cases (both DR and other conditions) was: sensitivity- 84.23% (95% CI- 82.63-85.84), specificity- 80.79% (95% CI- 79.05- 82.53). When we assessed whether AI matched any clinical diagnosis, be it referable or not, sensitivity was 85.67% (95% CI- 84.12-87.22), specificity was 98.86 (95% CI- 98.39-99.33), and AUC was 0.92 (95% CI- 0.91-0.94). ConclusionsThe integration of a portable device, AI analysis, and synchronous medical validation has the potential to play a crucial role in preventing blindness from DR, especially in socially unequal scenarios.