Search Results (7)

The development of microtextures has had a transformative impact on surface design in engineering, leading to substantial advancements in the performance, efficiency, and functionality of components and tools. This study presents an innovative methodology for fabricating SEDM electrodes. The methodology combines additive manufacturing by mask stereolithography with an optimized electroforming process to obtain high-precision copper shells. A key aspect of the study involved redesigning the electroforming equipment, enabling the independent examination of critical variables such as anode–cathode distance and electrolyte recirculation. This approach allowed precise analysis of their impact on metal deposition. This redesign enabled the assessment of the impact of electrolyte recirculation on the quality of the shells obtained. The findings indicate that continuous recirculation at 60% power effectively reduced thickness deviation by up to 32.5% compared to the worst-case scenario, achieving average thicknesses within the functional zone of approximately 110 µm. In contrast, the absence of flow or excessive turbulence did not generate defects such as unfilled zones or non-uniform thicknesses. The shells obtained were validated as functional tools in SEDM, demonstrating their viability for the generation of textures with high geometric fidelity. This approach optimizes the manufacturing of textured electrodes and opens new opportunities for their application in advanced industrial processes, providing a more efficient and sustainable alternative to conventional methods. Full article

Analyzing farmland landscape pattern variations induced by human activities can support effective decision making by governments to improve land use efficiency. However, research on long-term and continuous spatial process changes in farmland is scarce, and spatial pattern changes in farmlands remain insufficiently understood. Moreover, studies in which researchers have utilized dynamic process analysis to describe farmlands are relatively limited. This study aimed to apply the state-and-evolution detection model (SEDM), generated from long-term remote sensing data, to characterize farmland spatial pattern variations in Hengyang City, Hunan Province. Annual farmland data from 1990 to 2022, change type samples, and auxiliary data were collected, and six types of spatial pattern variations (perforation, dissection, shrinkage, creation, enlargement, and aggregation) were defined for the study area. Subsequently, the SEDM was applied based on four landscape indices. Finally, spatiotemporal evolution features, namely evolution times, evolution duration, and dominant evolution pattern, were quantified. The farmland in the study area exhibited a generally upward trend with fluctuations. The maximum area was followed by shrinkage (S), perforation (P), and enlargement (E). In over 70% of the study area, fewer than three evolution times occurred over three decades. The dominant evolution patterns were P–S, S–P, and E–P for single evolution events, and P–S–P, S–P–S, and P–S–S for double events. The model achieved an overall accuracy of 85%, thus demonstrating its effectiveness in characterizing landscape pattern variations and providing valuable insights for researchers and policy makers to develop strategies for farmland protection. Full article

A longitudinal design was used to examine the psychometric properties of the Self-Efficacy for Diabetes Self-Management (SEDM) for children and adolescents with a diagnosis of type 1 diabetes (T1D). The SEDM was adapted to Spanish and the best factorial solution was selected to test the invariance of the measures of age and gender. Individuals between the ages of 10 and 19 years old with a diagnosis of T1D completed a self-reported questionnaire (167 at Time 1 [mean age = 14.49, SD = 2.76; 56.9% boys] and 122 at Time 2 [mean age = 14.77, SD = 2.58; 56.6% boys]). Two unifactorial solutions were tested. The psychometric properties of the scale were validated. The proposed validation obtained excellent reliability indices (χ² (26) = 25.59, p > 0.49, RMSEA = 0.00, 95% CI [0.00, 0.07], CFI = 1.00, GFI = 0.96, AGFI = 0.92, TLI = 1.00, and CMIN = 0.98), and it appeared to be invariant for gender and for age groups. The Cronbach’s α was 0.85. The test–retest reliability was high (r = 0.69 [p < 0.001]). Convergent, discriminant, and external validity were proven. The nine-item SEDM is a brief measure with satisfactory structural validity. From our knowledge, this study provides the first reliable tool to assess self-efficacy in the management of T1D for Spanish children and adolescents. Full article

The transition towards a CO₂ neutral industry is currently spurring many new developments regarding processes for the conversion of CO₂, or CO₂-rich streams, into platform molecules such as methanol and dimethyl ether (DME). New processes give rise to new separation challenges, as well as novel opportunities for joint optimization of reaction and separation. In this context, the separation of CO₂ and DME can be performed very efficiently using the newly developed concept of stripping enhanced distillation (SED). SED is a distillation process that utilizes an additional stripping component (clearing gas) to promote the separation in the column. SED benefits from the utilization of the feedstock components as a clearing gas that can afterwards be recycled back to the conversion unit with the vapor distillate. Strongly improving the separation performance in the column, this approach also removes the need for external stripping mediums and, in addition, this recycling approach may significantly reduce the demand on the conversion unit upstream of SED. The benefits of using SED are demonstrated for two different processes for DME synthesis: (i) CO₂–DME separation after the sorption enhanced DME synthesis (SEDMES) process, using hydrogen as clearing gas, and (ii) CO₂–DME separation after direct DME synthesis via dry reforming (DIDR), using methane as a clearing gas. For the different cases, it is shown that, with minimal adaptations, the energy consumption for distillation is reduced by 20–30%, while product losses are minimized at the same time. Full article

Electrical discharge machining (EDM) can use soft tool electrodes to process hard workpieces to achieve “soft against hard”, because it directly uses electrical energy and thermal energy to remove metal materials. Then, it can generate complex features on harder materials and meet the requirements of excellent surface quality. Since EDM involves many process parameters, including electrical parameters, non-electrical parameters, and materials properties, it is essential to optimize its process parameters to obtain good performance. In this direction, the application of the swarm intelligence (SI) technique has become popular. In this paper, the existing literature is comprehensively reviewed, and the application of the SI technique in the optimization of EDM process parameters is summarized. Sinker-EDM (SEDM), wire-EDM (WEDM), and micro-EDM (MEDM) with various hybrid techniques are among the EDM methods considered in this study because of their broad adoption in industrial sections. The fundamental nature of all review articles will assist engineers/workers in determining the process parameters and processing performance, the SI algorithm, and the optimal technique by which to obtain the desired process parameters. In addition, discussions from the perspectives of the similarity, individuality, and complementarity of various SI algorithms are proposed, and necessary outlooks are predicted, which provides references for the high performance of the EDM processes in the future. Full article

Surface texturing has brought significant improvements in the functional properties of parts and components. Sinker electro discharge machining (SEDM) is one of the processes which generates great texturing results at different scale. An electrode is needed to reproduce the geometry to be textured. Some geometries are difficult or impossible to achieve on an electrode using conventional and even unconventional machining methods. This work sets out the advances made in the manufacturing of copper electrodes for electro erosion by additive manufacturing, and their subsequent application to the functional texturing of Al-Cu UNS A92024-T3 alloy. A combined procedure of digital light processing (DLP) additive manufacturing, sputtering and micro-electroforming (AMSME), has been used to produce electrodes. Also, a specific laboratory equipment has been developed to reproduce details on a microscopic scale. Shells with outgoing spherical geometries pattern have been manufactured. AMSME process has shown ability to copper electrodes manufacturing. A highly detailed surface on a micrometric scale have been achieved. Copper shells with minimum thickness close to 300 µm have been tested in sinker electro discharge machining (SEDM) and have been shown very good performance in surface finishing operations. The method has shown great potential for use in surfaces texturing. Full article

The development of prediction tools for production performance and the lifespan of shale gas reservoirs has been a focus for petroleum engineers. Several decline curve models have been developed and compared with data from shale gas production. To accurately forecast the estimated ultimate recovery for shale gas reservoirs, consistent and accurate decline curve modelling is required. In this paper, the current decline curve models are evaluated using the goodness of fit as a measure of accuracy with field data. The evaluation found that there are advantages in using the current DCA models; however, they also have limitations associated with them that have to be addressed. Based on the accuracy assessment conducted on the different models, it appears that the Stretched Exponential Decline Model (SEDM) and Logistic Growth Model (LGM), followed by the Extended Exponential Decline Model (EEDM), the Power Law Exponential Model (PLE), the Doung’s Model, and lastly, the Arps Hyperbolic Decline Model, provide the best fit with production data. Full article