Analisa Perhitungan dan Pengaturan Relai Arus Lebih dan Relai Gangguan Tanah pada Kubikel Cakra 20 KV di PT XYZ

Gangguan hubung singkat fasa ke tanah dan fasa-fasa merupakan salah satu permasalahan yang mungkin timbul dalam pengoperasian transformator daya dalam sebuah Gardu Induk. Gangguan yang disebabkan oleh adanya hubung singkat menimbulkan banyak kerugian, kerugian pada sistem transmisi kelistrikan maupun kerugian di pihak konsumen energi listrik. Salah satu cara untuk mengatasi gangguan ini adalah dengan memasang peralatan pengaman pada transformator. Relai arus lebih merupakan relai proteksi yang bekerja dengan Pemutus Tenaga (Circuit Breaker). Pada tulisan ini diberikan perhitungan setting relay arus lebih dan relay tanah pada pada penyulang keluar dari kubikel Cakra 20 kV di sebuah Perusahaan, yang karena alasan privacy disebutkan sebagai PT XYZ. Analisa yang dilakukan menunjukkan bahwa setting relay arus lebih dan relay tanah eksisting telah sesuai dengan standar yang berlaku

Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Linear attention is an efficient attention mechanism that has recently emerged as a promising alternative to conventional softmax attention. With its ability to process tokens in linear computational complexities, linear attention, in theory, can handle sequences of unlimited length without sacrificing speed, i.e., maintaining a constant training speed for various sequence lengths with a fixed memory consumption. However, due to the issue with cumulative summation (cumsum), current linear attention algorithms cannot demonstrate their theoretical advantage in a causal setting. In this paper, we present Lightning Attention-2, the first linear attention implementation that enables linear attention to realize its theoretical computational benefits. To achieve this, we leverage the thought of tiling, separately handling the intra-block and inter-block components in linear attention calculation. Specifically, we utilize the conventional attention computation mechanism for the intra-blocks and apply linear attention kernel tricks for the inter-blocks. A tiling technique is adopted through both forward and backward procedures to take full advantage of the GPU hardware. We implement our algorithm in Triton to make it IO-aware and hardware-friendly. Various experiments are conducted on different model sizes and sequence lengths. Lightning Attention-2 retains consistent training and inference speed regardless of input sequence length and is significantly faster than other attention mechanisms. The source code is available at https://github.com/OpenNLPLab/lightning-attention.Comment: Technical Report. Yiran Zhong is the corresponding author. The source code is available at https://github.com/OpenNLPLab/lightning-attentio

Box2Poly: Memory-Efficient Polygon Prediction of Arbitrarily Shaped and Rotated Text

Recently, Transformer-based text detection techniques have sought to predict polygons by encoding the coordinates of individual boundary vertices using distinct query features. However, this approach incurs a significant memory overhead and struggles to effectively capture the intricate relationships between vertices belonging to the same instance. Consequently, irregular text layouts often lead to the prediction of outlined vertices, diminishing the quality of results. To address these challenges, we present an innovative approach rooted in Sparse R-CNN: a cascade decoding pipeline for polygon prediction. Our method ensures precision by iteratively refining polygon predictions, considering both the scale and location of preceding results. Leveraging this stabilized regression pipeline, even employing just a single feature vector to guide polygon instance regression yields promising detection results. Simultaneously, the leverage of instance-level feature proposal substantially enhances memory efficiency (>50% less vs. the state-of-the-art method DPText-DETR) and reduces inference speed (>40% less vs. DPText-DETR) with minor performance drop on benchmarks

Calcium-magnesium-alumino-silicate induced degradation of La2(Zr0.7Ce0.3)2O7/YSZ double-ceramic–layer thermal barrier coatings prepared by electron beam-physical vapor deposition

During last decades, much effort has been made to develop new alternative thermal barrier coating (TBC) to traditional YSZ for applications above 1250oC. La2(Zr0.7Ce0.3)2O7(LZ7C3) is deemed as a very promising TBC candidate for advanced gas turbine because of its extremely low thermal conductivity, high sintering resistance and phase stability from room temperature to 1600oC. Thermal cycling with a gas burner showed that the LZ7C3/YSZ double-ceramic-layer (DCL) coatings prepared by electron beam-physical vapor deposition (EB-PVD) or atmospheric plasma spraying had a much longer lifetime than that of YSZ coating at 1250± 50oC.The use of the new TBC can allow higher gas temperatures, resulting in further improved thermal efficiency and engine performance. However, at these high operating temperatures, TBCs become susceptible to attack by calcium-magnesium-alumino-silicate (CMAS, relative to the main chemical components Ca, Mg, Al and Si) deposits resulting from the ingestion of siliceous minerals (dust, sand, volcanic ash, runway debris) with the intake air. CMAS becomes molten at temperatures above 1200oC and then rapidly penetrates the TBCs by capillary force, resulting in the loss of strain tolerance and premature failure of the coatings. In this paper, CMAS induced degradation of LZ7C3/YSZ DCL coatings prepared by EB-PVD method were investigated. Hot corrosion tests were performed at 1250oC at durations varying from 0.5 h to 24 h. It is observed that the infiltration of CMAS in the intercolumnar gaps was largely suppressed in the case of EB-PVD LZ7C3 coating. The penetration depth rarely exceeded 40 μm below the original surface even after 24 h exposure at 1250oC. This was ascribed to rapid dissolution of the LZ7C3 and essentially concurrent formation of a sealing layer made of crystalline apatite and fluorite phases, which is consistent with the observation on Gd2Zr2O7. However, large vertical cracks would form in the EB-PVD LZ7C3 coating during thermal cycling as a result of re-crystallization, sintering and thermal expansion mismatch between ceramic coating and substrate. These vertical cracks can also act as channels to CMAS melt infiltration. Since the kinetics of the dissolve-reprecipitation reaction was slower than the infiltration rate of CMAS in the vertical crack, the majority of vertical cracks were not sealed. As a result, CMAS flowed down to the LZ7C3/YSZ interface along the vertical cracks, and then easily penetrated the YSZ buffer layer by capillary force. Chemical interaction also occurred in the YSZ buffer layer. What\u27s more, the YSZ layer in the DCL coating even underwent a severer CMAS attack than the single YSZ coating. After 4 h CMAS exposure, the YSZ layer of the LZ7C3/YSZ bilayer coating was totally dissolved by molten CMAS followed by precipitation of a large number of globular ZrO2 particles, while the single YSZ coating just suffered a slight degradation in the same experimental conditions and still kept its columnar structure. The probable reason was that the CMAS melt in the YSZ layer of the DCL coating had a higher CaO/SiO2 ration than the original CMAS composition due to the formation of apatite phase when CMAS reacted with the upper LZ7C3 layer. The initial Si: Ca ratio (Si: Ca≈1.4) in CMAS melt is less than the corresponding apatite (Si: Ca≈3), leading to progressive CaO enrichment during apatite crystallization. For this reason, it is suggested that the effectiveness of the CMAS mitigation strategy for YSZ TBCs by adopting a so-called CMAS-resistant top layer needs to be assessed in the context of more realistic conditions. If the formation of large vertical cracks in TBCs was not avoided, this CMAS mitigation approach may not as effective as expected

Quantitative index of EIT based on 3D abdominal bleeding simulation model

According CT images, a 3D abdominal bleeding simulation model with real shape was set up using COMOSOL Multi-physics. By parameter sweeping, the surface measurement data for EIT were obtained while bleeding from 0~800ml. Total relative changes (TRC) of the data were calculated, shown a linear correlation (R>0.99) with bleeding volume (BV), which implies TRC be a good quantitative index to indicate BV

Process Monitoring and Fault Diagnosis for Shell Rolling Production of Seamless Tube

Continuous rolling production process of seamless tube has many characteristics, including multiperiod and strong nonlinearity, and quickly changing dynamic characteristics. It is difficult to build its mechanism model. In this paper we divide production data into several subperiods by -means clustering algorithm combined with production process; then we establish a continuous rolling production monitoring and fault diagnosis model based on multistage MPCA method. Simulation experiments show that the rolling production process monitoring and fault diagnosis model based on multistage MPCA method is effective, and it has a good real-time performance, high reliability, and precision

TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer

We present TransNormerLLM, the first linear attention-based Large Language Model (LLM) that outperforms conventional softmax attention-based models in terms of both accuracy and efficiency. TransNormerLLM evolves from the previous linear attention architecture TransNormer by making advanced modifications that include positional embedding, linear attention acceleration, gating mechanisms, tensor normalization, and inference acceleration and stabilization. Specifically, we use LRPE together with an exponential decay to avoid attention dilution issues while allowing the model to retain global interactions between tokens. Additionally, we propose Lightning Attention, a cutting-edge technique that accelerates linear attention by more than twice in runtime and reduces memory usage by a remarkable four times. To further enhance the performance of TransNormer, we leverage a gating mechanism for smooth training and a new tensor normalization scheme to accelerate the model, resulting in an impressive acceleration of over $20\%$. Furthermore, we develop a robust inference algorithm that ensures numerical stability and consistent inference speed, regardless of the sequence length, showcasing superior efficiency during both training and inference stages. We also implement an efficient model parallel schema for TransNormerLLM, enabling seamless deployment on large-scale clusters and facilitating expansion to even more extensive models, i.e., LLMs with 175B parameters. We validate our model design through a series of ablations and train models with sizes of 385M, 1B, and 7B on our self-collected corpus. Benchmark results demonstrate that our models not only match the performance of state-of-the-art LLMs with Transformer but are also significantly faster. Code is released at: https://github.com/OpenNLPLab/TransnormerLLM.Comment: Technical Report. Yiran Zhong is the corresponding author. Zhen Qin, Dong Li, Weigao Sun, Weixuan Sun, Xuyang Shen contribute equally to this paper. Code is released at: https://github.com/OpenNLPLab/TransnormerLL

Authentication method of sea duck eggs based on targeted metabolomics

Objective A targeted metabolomics based on gas chromatography-mass spectrometry (GC-MS) was established for the authentication of sea duck eggs. Methods In this study, gas chromatography-mass spectrometry was used to characterize the fat acid profiles of sea duck eggs and cage duck eggs. Chemometrics was used to analyze the difference between sea duck eggs and cage duck eggs to screen the markers that could be used to identify the authenticity of sea duck eggs. Results Omega-3 fatty acids (Ω-3) in sea duck eggs account for a higher proportion of total fatty acids than cage duck eggs, and there were significant differences (t=23.58, P<0.05). Sea duck eggs and cage duck eggs were distinguished by principal component analysis. Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were screened by orthogonal partial least squares discriminant analysis that contributed the most to the difference of sea duck eggs and cage duck eggs. EPA was detected only in sea duck eggs, and the content of DHA in sea duck eggs was higher than that of cage duck eggs. Conclusion This study showed that EPA and DHA can be used as a reliable marker to authenticate sea duck eggs

Analysis of Flow Behavior for Acid Fracturing Wells in Fractured-Vuggy Carbonate Reservoirs

This study develops a mathematical model for transient flow analysis of acid fracturing wells in fractured-vuggy carbonate reservoirs. This model considers a composite system with the inner region containing finite number of artificial fractures and wormholes and the outer region showing a triple-porosity medium. Both analytical and numerical solutions are derived in this work, and the comparison between two solutions verifies the model accurately. Flow behavior is analyzed thoroughly by examining the standard log-log type curves. Flow in this composite system can be divided into six or eight main flow regimes comprehensively. Three or two characteristic V-shaped segments can be observed on pressure derivative curves. Each V-shaped segment corresponds to a specific flow regime. One or two of the V-shaped segments may be absent in particular cases. Effects of interregional diffusivity ratio and interregional conductivity ratio on transient responses are strong in the early-flow period. The shape and position of type curves are also influenced by interporosity coefficients, storativity ratios, and reservoir radius significantly. Finally, we show the differences between our model and the similar model with single fracture or without acid fracturing and further investigate the pseudo-skin factor caused by acid fracturing