Nextrex Overview DC MicroGrid

When Thomas Edison first began devising ways to bring electricity into the average American
home more than 100 years ago, he proposed Direct Current as the means for delivering it. DC
was far safer and easier to produce than Alternating Current. But DC didn’t travel well, and
utilities eventually chose AC to transmit power.
For fifty years AC served the nation’s needs. But a scientific breakthrough—the
semiconductor—was developed that made many of our modern technological advancements
possible. Trouble was, semiconductors require DC power. To get around that issue, we currently
convert AC power to DC for our computer equipment, appliances and other devices, and lose a
significant percentage of that power in the process as heat.
Wouldn’t it be simpler to just use DC power outright? Many developers and businesspeople
think so and have begun to turn to Direct Current solutions when designing or renovating
building electrical systems and certain exterior lighting and signage applications. These DC
design solutions can be used lieu of or in addition to AC power.
Nextek Power Systems, Inc. is a pioneer in DC power networks for buildings. Our technology is
focused on designing and implementing building power systems that incorporate the latest and
best in renewable energy sources with existing grid power. By creating these strategies to
eliminate the need for conversion, we can substantially reduce energy costs, while increasing
reliability.

Tantangan Photovoltaic Indonesia versi APAMSI

INTERVIEW
SEKRETARIS JENDERAL
ASOSIASI PABRIKAN MODUL SURYA INDONESIA
(APAMSI)
1. Saat ini terdapat 8 pabrik perakitan modul surya di Indonesia, namun baru 5
perusahaan yang menjadi anggota APAMSI yaitu PT. LEN Industri (Persero),
PT. Surya Utama Putra, PT. Swadaya Prima Utama, PT. Adyawinsa Electrical &
Power, PT. Azet Surya Lestari dan PT. Wijaya Karya Intrade Energi.
2. Pabrikasi panel surya merupakan industri energi surya yang mempunyai resiko
paling kecil dibandingkan industri sel surya, industri wafer dst. Resiko ini terkait
biaya investasi yang dibutuhkan sedangkan permintaan industri di dalam negeri
masih rendah.
3. Produksi rata-rata anggota APAMSI adalah 16% dari total kapasitas produksi
karena masih mengandalkan proyek pemerintah. Akibatnya, pabrik hanya
bekerja pada bulan Agustus – Desember tiap tahunnya.
4. Pemerintah sebenarnya membuat pasar yang lebih besar yaitu lelang kuota
energi surya 140 MW di 82 lokasi sebagai bentuk implementasi Permen ESDM
17/2013 ttg Pembelian Tenaga Listrik oleh PT. PLN dari Pembangkit Listrik
Tenaga Surya Fotovoltaik;
5. Dengan target kapasitas 140MW tersebut, maka Indonesia layak membuat
industri sel surya di dalam negeri. Bila target ditingkatkan menjadi 500MW maka
layak dibangun industri wafer silika di dalam negeri selanjutnya jika target
menjadi 1 GW maka industri energi surya dalam negeri mampu menyerap
bahan mineral, nikel dan sebagainya untuk bahan baku panel surya.
6. Mineral nikel Indonesia selama ini diekspor di Cina untuk kemudian diproses
lebih lanjut menjadi silika → ingot → silikon → wafer → sel surya yang kemudian
diekspor kembali ke Indonesia untuk dirakit menjadi panel surya;
7. Untuk memaksa produsen membuka pabriknya di dalam negeri dapat meniru
langkah Malaysia yang melarang impor PLTS. Cara lain yang dapat dilakukan
adalah pelarangan expor mineral sehingga produsen akan bangun smelter di
dalam negeri dan kemudian expor ingot yang dihasilkan. Setelah itu, pemerintah
perlu keluarkan larangan expor ingot untuk paksa produsen produksi wafer di
dalam negeri.
8. Terkait lelang kuota PLTS, APAMSI tidak bisa berkompetisi dengan PLTS china
yang mempunyai kapasitas produksi 3,7 GW per tahun. China pun melakukan
dumping harga karena harga impor sel surya $0,697/W sedangkan harga impor
panel surya jadi $0,7/W. Akibatnya adalah :
CKD (Komponen panel surya?) Panel surya
FOB China ($/W) 0.697 0.7
CNF Tj. Priok 0.8 0.8
+BM, PPn, PPj Sel = 0%
Silin = 20%
ALE =10%
TGU=15%
0%
On truk ($/W) 1,1 – 1,2 0.8
9. Panel surya Cina sudah dikenakan sanksi dumping dan hal ini perlu ditiru oleh
Indonesia dengan sanksi sehingga harga panel surya cina menjadi $1,9/W. Hal
ini diperlukan karena biaya produksi APAMSI sebesar $1,3 – 1,5.
10. Kaca panel surya pun sebenarnyad bisa diproduksi di dalam negeri (contohnya
ASAHI) namun belum bisa melayani permintaan APAMSI yang dinilai terlalu
kecil yaitu volume 1 x produksi kaca setara engan volume penjualan APAMSI
selama 3 tahun.
11. Standarisasi SNI tidak bisa menutup impor PLTS Cina karena selama ini panel
surya Cina sudah memenuhi berbagai standar internasional dalam rangka
memasok kebutuhan Eropa.
12. Pemerintah sudah larang PLTS impor untuk proyek APBN namun masih
memperbolehkan untuk proyek kuota dengan syarat TKDN minimal 40%.
13. APAMSI merekomendasikan teknologi kristalin yang padat karya dan bahan
baku yang melimpah walau belum bisa diproduksi di dalam negeri. Teknologi
thin film memang mempunyai biaya produksi yang lebih murah namun
mempunyai efisiensi yang rendah. Selain itu, industri thin film adalah industri
padat modal dengan investasi sekitar $ 55 juta/ mesin untuk kapasitas 50 MW/
tahun. Pada saat ada teknologi thin film dengan efisiensi yang lebih baik, maka
industri harus ganti seluruh peralatan karena siste produksinya adalah inline.
14. APAMSI membutuhkan teknologi micro inverter dan in-charge untuk PLTS.
Industri pendukungnya seperti panel, trafo dan PCB sudah ada di dalam negeri.
15. TKDN Baterai buatan Nipres juga sudah mencapai 48%.
16. Penjelasan singkat mengenai kuota PLTS (Permen ESDM 17/2003) :
a. Kuota Kapasitas PLTS Fotovoltaik adalah jumlah maksimum kapasitas PLTS Fotovoltaik yang dapat
diinterkoneksikan pada suatu sistem/ subsistem Jarlngan tenaga listrik milik PLN.
b. Pemerintah menugaskan PLN untuk membeli tenaga listrik dari PLTS Fotovoltaik.
c. PLN wajib membeli seluruh tenaga listrik yang dihasilkan dari PLTS Fotovoltaik dari badan usaha
(BUMN, BUMD, swasta, dan koperasi) yang ditetapkan sebagai pemenang lelang Kuota Kapasitas.
d. Pembelian tenaga listrik dari PLTS Fotovoltaik untuk semua kapasitas terpasang ditetapkan dengan
harga patokan tertinggi sebesar US$ 25 sen/kWh.
e. Pembelian tenaga listrik, jika PLTS Fotovoltaik menggunakan modul fotovoltaik TKDN sekurangkurangnya 40%, diberikan insentif dan ditetapkan dengan harga patokan tertinggi sebesar US$ 30
sen/ kWh.
f. Harga patokan tertinggi sudah termasuk seluruh biaya interkoneksi dari PLTS Fotovoltaik ke titik
interkoneksi di jaringan tenaga listrik PLN.

Datasheet-AL-6063-T5

GENERAL INFORMATION
Alloy 6063 is a heat-treatable alloy having good combination of extrudability and mechanical properties, also responding well to
polishing, anodizing, chemical brightening and dyeing.
Thin-walled hollows and intricate solid shapes could be produced more readily and easily with this alloy.
ALLOY 6063
Aluminium-Magnesium-Silicon alloy (AlMgSiO)
Chemical Composition
%Si       %Fe %Cu  %Cu  %Mn      %Mg      %Cr  %Zn      %Ti      %Other    %Aluminium
0.35–0.50    0.10–0.30    0.10  0.10     0.35–0.55       0.05      0.10      0.10    0.05   Remainder
Mechanical Properties
Temper    Ultimate Tensile Strength (MPa)    0.2%Proof Stress (MPa)    % Elongation
T4    130          69        14
T5    150          110        7
T6    185          160        7
Physical Properties
Density              2.71 X 10⁻⁶ kg/mm³
Melting Range            600 – 650 °C
Specific Heat between 0 - 100°C        879 J/kg °C
Coefficient of linear expansion between 20 - 100°C  
Thermal Conductivity at 25°C        23 X 10⁻⁶ / °C
Electrical Resistivity at 20°C        0.033Ωm
Modulus of Elasticity          69 X 103 MPa
Temper Designation
F -   Indicates the as-fabricated condition where to control has been exercised over the temper of the alloy.
T -  Indicates the heat treated alloy.
T4 -  Solution heat treatment followed by natural ageing at room temperature to a substantial stable condition.
T5 -  Artificial ageing after an elevated temperature, rapid cooling fabrication process such as casting or extrusion.
T6 -  Solution heat treatment followed by artificial ageing.
For subsequent severe forming process as in bending, please opt for softer tempers.
Mill Finish
Natural aluminium finish of the extrusion-press with no further anodizing or coloring process.
Natural Anidizing Finish
By  means  of  electro-chemical  process  natural oxide-film  will  be  formed  and  thickened  considerably  on  the  metal  surface.  The
aluminium extrusion is then sealed in hot deionised-water which closes of the pores and permanently seals the oxide film imparting
to the metal surface the extreme hardness, corrosion and wear resistance of the oxide.
Alexindo  natural  anodized  finish  conform  to  International Standard  an  is  available  in  nominal  film-thickness  of  5,  10,  18  and  25
microns.
For normal and severe atmospheric condition, film thickness of 10 and 25 microns respectively should be recommended.
Colour Finish
In Alexindo colour process, inorganic metal colour particles are deposited and fixed electrolytically at the very base of the process of
anodic pores of anodic film allowing virtually full thickness off the anodic film to protect them.
The  aluminium  extrusion is  then  sealed in  hot  deionised water  which  closes off  the  pores  and  permanently  sealed in  the  colour
particles.
The  colouring  process  in combination  with anodizing is  to  yield  a  finish  which  is  lightfast,  abrasion  and  corrosion  resistance  and
unchanging colour intensity.
For normal and severe atmospheric condition, film thickness of 18 and 25 microns respectively should be recommended.

Solar Mounting

1.Roof top.

Use Rail bracket & fastener. Clamp solar modul (midle&End) and screw bracket. Cost average 0.08USD/WP.

2.Ground Mounting.

Using Metal-Or Aluminium & can combination material. usually Alluminium alloy series 6060-T6 or 6063-T5. metal finishing with hot dipped galvanish. Cost average for mounting only 0,01-0,018USD/WP.
Screw stainless for maximum life time. System can isntal to ground with 3 Type:
 a. Pile screw.

Can aplied with large scale. Sample Krinner frace operate semi robotic screw to support instalation.

 b.Pilling.

Schelter have good technology about pilling technologies on PV. Can Aply on soft land for large scale MW PV with fast & Robust.
c.Concret foundation. Can Aplication on the small scale Kw. have good social impact for increase worker.

3.Tracker system. Adding solar tracker can be aplied on the ground mounting only. for single axis can increase production energy average 15%. For dual axis can increase Energy dayli average 25-40%.

Metal + Aluminium Extrude Battrey Rack

1.

Battrey Rack With Fast Production & Robust design. Up to 800kg/Rack. Can Compare Quality & cost With passoni Alfa italia. Similar design but difference proces & Metode. . Can Use Battrey type OPZV 2V800Ah & OPZV2V1000Ah. Material Al 6063T-T5 finishing with Anodized for anti corotion. Metal ST 41 with powder coating.

Introduction To Robust Design (Taguchi Method)

Profile photo of Madhav S. PhadkeMadhav S. Phadke 7 Robust Design method, also called the Taguchi Method, pioneered by Dr. Genichi Taguchi, greatly improves engineering productivity. By consciously considering the noise factors (environmental variation during the product’s usage, manufacturing variation, and component deterioration) and the cost of failure in the field the Robust Design method helps ensure customer satisfaction. Robust Design focuses on improving the fundamental function of the product or process, thus facilitating flexible designs and concurrent engineering. Indeed, it is the most powerful method available to reduce product cost, improve quality, and simultaneously reduce development interval. 1. Why Use Robust Design Method? Over the last five years many leading companies have invested heavily in the Six Sigma approach aimed at reducing waste during manufacturing and operations. These efforts have had great impact on the cost structure and hence on the bottom line of those companies. Many of them have reached the maximum potential of the traditional Six Sigma approach. What would be the engine for the next wave of productivity improvement? Brenda Reichelderfer of ITT Industries reported on their benchmarking survey of many leading companies, “design directly influences more than 70% of the product life cycle cost; companies with high product development effectiveness have earnings three times the average earnings; and companies with high product development effectiveness have revenue growth two times the average revenue growth.” She also observed, “40% of product development costs are wasted!” These and similar observations by other leading companies are compelling them to adopt improved product development processes under the banner Design for Six Sigma. The Design for Six Sigma approach is focused on 1) increasing engineering productivity so that new products can be developed rapidly and at low cost, and 2) value based management. Robust Design method is central to improving engineering productivity. Pioneered by Dr. Genichi Taguchi after the end of the Second World War, the method has evolved over the last five decades. Many companies around the world have saved hundreds of millions of dollars by using the method in diverse industries: automobiles, xerography, telecommunications, electronics, software, etc. 1.1. Typical Problems Addressed By Robust Design A team of engineers was working on the design of a radio receiver for ground to aircraft communication requiring high reliability, i.e., low bit error rate, for data transmission. On the one hand, building series of prototypes to sequentially eliminate problems would be forbiddingly expensive. On the other hand, computer simulation effort for evaluating a single design was also time consuming and expensive. Then, how can one speed up development and yet assure reliability? In an another project, a manufacturer had introduced a high speed copy machine to the field only to find that the paper feeder jammed almost ten times more frequently than what was planned. The traditional method for evaluating the reliability of a single new design idea used to take several weeks. How can the company conduct the needed research in a short time and come up with a design that would not embarrass the company again in the field? The Robust Design method has helped reduce the development time and cost by a factor of two or better in many such problems. In general, engineering decisions involved in product/system development can be classified into two categories: Error-free implementation of the past collective knowledge and experience Generation of new design information, often for improving product quality/reliability, performance, and cost. While CAD/CAE tools are effective for implementing past knowledge, Robust Design method greatly improves productivity in generation of new knowledge by acting as an amplifier of engineering skills. With Robust Design, a company can rapidly achieve the full technological potential of their design ideas and achieve higher profits. 2. Robustness Strategy Variation reduction is universally recognized as a key to reliability and productivity improvement. There are many approaches to reducing the variability, each one having its place in the product development cycle. By addressing variation reduction at a particular stage in a product’s life cycle, one can prevent failures in the downstream stages. The Six Sigma approach has made tremendous gains in cost reduction by finding problems that occur in manufacturing or white-collar operations and fixing the immediate causes. The robustness strategy is to prevent problems through optimizing product designs and manufacturing process designs. The manufacturer of a differential op-amplifier used in coin telephones faced the problem of excessive offset voltage due to manufacturing variability. High offset voltage caused poor voice quality, especially for phones further away from the central office. So, how to minimize field problems and associated cost? There are many approaches: Compensate the customers for their losses. Screen out circuits having large offset voltage at the end of the production line. Institute tighter tolerances through process control on the manufacturing line. Change the nominal values of critical circuit parameters such that the circuit’s function becomes insensitive to the cause, namely, manufacturing variation. The approach 4 is the robustness strategy. As one moves from approach 1 to 4, one progressively moves upstream in the product delivery cycle and also becomes more efficient in cost control. Hence it is preferable to address the problem as upstream as possible. The robustness strategy provides the crucial methodology for systematically arriving at solutions that make designs less sensitive to various causes of variation. It can be used for optimizing product design as well as for manufacturing process design. The Robustness Strategy uses five primary tools: P-Diagram is used to classify the variables associated with the product into noise, control, signal (input), and response (output) factors. Ideal Function is used to mathematically specify the ideal form of the signal-response relationship as embodied by the design concept for making the higher-level system work perfectly. Quadratic Loss Function (also known as Quality Loss Function) is used to quantify the loss incurred by the user due to deviation from target performance. Signal-to-Noise Ratio is used for predicting the field quality through laboratory experiments. Orthogonal Arrays are used for gathering dependable information about control factors (design parameters) with a small number of experiments. 2.1 P-Diagram

P-Diagram is a must for every development project. It is a way of succinctly defining the development scope. First we identify the signal (input) and response (output) associated with the design concept. For example, in designing the cooling system for a room the thermostat setting is the signal and the resulting room temperature is the response. Next consider the parameters/factors that are beyond the control of the designer. Those factors are called noise factors. Outside temperature, opening/closing of windows, and number of occupants are examples of noise factors. Parameters that can be specified by the designer are called control factors. The number of registers, their locations, size of the air conditioning unit, insulation are examples of control factors. Ideally, the resulting room temperature should be equal to the set point temperature. Thus the ideal function here is a straight line of slope one in the signal-response graph. This relationship must hold for all operating conditions. However, the noise factors cause the relationship to deviate from the ideal. The job of the designer is to select appropriate control factors and their settings so that the deviation from the ideal is minimum at a low cost. Such a design is called a minimum sensitivity design or a robust design. It can be achieved by exploiting nonlinearity of the products/systems. The Robust Design method prescribes a systematic procedure for minimizing design sensitivity and it is called Parameter Design. An overwhelming majority of product failures and the resulting field costs and design iterations come from ignoring noise factors during the early design stages. The noise factors crop up one by one as surprises in the subsequent product delivery stages causing costly failures and band-aids. These problems are avoided in the Robust Design method by subjecting the design ideas to noise factors through parameter design. The next step is to specify allowed deviation of the parameters from the nominal values. It involves balancing the added cost of tighter tolerances against the benefits to the customer. Similar decisions must be made regarding the selection of different grades of the subsystems and components from available alternatives. The quadratic loss function is very useful for quantifying the impact of these decisions on customers or higher-level systems. The process of balancing the cost is called Tolerance Design. The result of using parameter design followed by tolerance design is successful products at low cost. 2.2 Quality Measurement In quality improvement and design optimization the metric plays a crucial role. Unfortunately, a single metric does not serve all stages of product delivery. It is common to use the fraction of products outside the specified limits as the measure of quality. Though it is a good measure of the loss due to scrap, it miserably fails as a predictor of customer satisfaction. The quality loss function serves that purpose very well. Let us define the following variables: m: target value for a critical product characteristic +/- Delta0: allowed deviation from the target A0: loss due to a defective product Then the quality loss, L, suffered by an average customer due to a product with y as value of the characteristic is given by the following equation: L = k * ( y – m )2 where k = ( A0 / Delta02 ) If the output of the factory has distribution of the critical characteristic with mean m and variance s2, then the average quality loss per unit of the product is given by: Q = k { ( mu – m )2 + sigma2 } 2.3 Signal To Noise (S/N) Ratios The product/process/system design phase involves deciding the best values/levels for the control factors. The signal to noise (S/N) ratio is an ideal metric for that purpose. The equation for average quality loss, Q, says that the customer’s average quality loss depends on the deviation of the mean from the target and also on the variance. An important class of design optimization problem requires minimization of the variance while keeping the mean on target. Between the mean and standard deviation, it is typically easy to adjust the mean on target, but reducing the variance is difficult. Therefore, the designer should minimize the variance first and then adjust the mean on target.Among the available control factors most of them should be used to reduce variance. Only one or two control factors are adequate for adjusting the mean on target. The design optimization problem can be solved in two steps: 1. Maximize the S/N ratio, h, defined as h = 10 log10 ( h2~ / sigma2 ) This is the step of variance reduction. 2. Adjust the mean on target using a control factor that has no effect on h. Such a factor is called a scaling factor. This is the step of adjusting the mean on target. One typically looks for one scaling factor to adjust the mean on target during design and another for adjusting the mean to compensate for process variation during manufacturing. 2.4 Static Versus Dynamic S/N Ratios In some engineering problems, the signal factor is absent or it takes a fixed value. These problems are called Static problems and the corresponding S/N ratios are called static S/N ratios. The S/N ratio described in the preceding section is a static S/N ratio. In other problems, the signal and response must follow a function called the ideal function. In the cooling system example described earlier, the response (room temperature) and signal (set point) must follow a linear relationship. Such problems are called dynamic problems and the corresponding S/N ratios are called dynamic S/N ratios. The dynamic S/N ratio will be illustrated in a later section using a turbine design example. Dynamic S/N ratios are very useful for technology development, which is the process of generating flexible solutions that can be used in many products. 3. Steps in Robust Parameter Design Robust Parameter design has 4 main steps: 1. Problem Formulation: This step consists of identifying the main function, developing the P-diagram, defining the ideal function and S/N ratio, and planning the experiments. The experiments involve changing the control, noise and signal factors systematically using orthogonal arrays. 2. Data Collection/Simulation: The experiments may be conducted in hardware or through simulation. It is not necessary to have a full-scale model of the product for the purpose of experimentation. It is sufficient and more desirable to have an essential model of the product that adequately captures the design concept. Thus, the experiments can be done more economically. 3. Factor Effects Analysis: The effects of the control factors are calculated in this step and the results are analyzed to select optimum setting of the control factors. 4. Prediction/Confirmation: In order to validate the optimum conditions we predict the performance of the product design under baseline and optimum settings of the control factors. Then we perform confirmation experiments under these conditions and compare the results with the predictions. If the results of confirmation experiments agree with the predictions, then we implement the results. Otherwise, the above steps must be iterated.

Datasheet SUS 304-AISI 304

AISI Type 304 Stainless Steel Subcategory: Ferrous Metal; Heat Resisting; Metal; Stainless Steel; T 300 Series Stainless Steel Close Analogs: UNS S30400; AMS 5501, 5513, 5560, 5565; ASME SA182, SA194 (8), SA213, SA240; ASTM A167, A182, A193, A194 Key Words: aisi304, aisi 304, T304, T 304, SUS304, SS304, 304SS, 304 SS, UNS S30400, AMS 5501, AMS 5513, AMS 5560, AMS 5565, AMS 5566, AMS 5567, AMS 5639, AMS 5697, ASME SA182, ASME SA194 (8), ASME SA213, ASME SA240, ASME SA249, ASME SA312, ASME SA320 (B8), ASME SA358, ASME SA376, ASME SA403, ASME SA409, ASME SA430, ASME SA479, ASME SA688, ASTM A167, ASTM A182, ASTM A193, ASTM A194, ASTM A666, FED QQ-S-763, MILSPEC MIL-S-5059, SAE 30304, DIN 1.4301, X5CrNi189, B.S. 304 S 15, EN 58E, PN 86020 (Poland), OH18N9, ISO 4954 X5CrNi189E, ISO 683/13 11, 18-8 Component Wt. % C Max 0.08 Cr 18 - 20 Fe 66.345 - 74 Mn Max 2 Ni 8 - 10.5 P Max 0.045 S Max 0.03 Si Max 1 Material Notes: Austenitic Cr-Ni stainless steel. Better corrosion resistance than Type 302. High ductility, excellent drawing, forming, and spinning properties. Essentially non-magnetic, becomes slightly magnetic when cold worked. Low carbon content means less carbide precipitation in the heat-affected zone during welding and a lower susceptibility to intergranular corrosion. Applications:beer kegs, bellows, chemical equipment, coal hopper linings, cooking equipment, cooling coils, cryogenic vessels, dairy equipment, evaporators, flatware utensils, feedwater tubing, flexible metal hose, food processing equipment, hospital surgical equipment, hypodermic needles, kitchen sinks, marine equipment and fasteners, nuclear vessels, oil well filter screens, refrigeration equipment, paper industry, pots and pans, pressure vessels, sanitary fittings, valves, shipping drums, spinning, still tubes, textile dyeing equipment, tubing. Corrosion Resistance: resists most oxidizing acids and salt spray. Physical Properties Metric English Comments Density 8 g/cc 0.289 lb/in³ Mechanical Properties Hardness, Brinell 123 123 Converted from Rockwell B hardness. Hardness, Knoop 138 138 Converted from Rockwell B hardness. Hardness, Rockwell B 70 70 Hardness, Rockwell B 70 70 Hardness, Vickers 129 129 Converted from Rockwell B hardness. Tensile Strength, Ultimate 505 MPa 73200 psi Tensile Strength, Yield 215 MPa 31200 psi at 0.2% offset Elongation at Break 70 % 70 % in 50 mm Modulus of Elasticity 193 - 200 GPa 28000 - 29000 ksi Poisson's Ratio 0.29 0.29 Charpy Impact 325 J 240 ft-lb Shear Modulus 86 GPa 12500 ksi Electrical Properties Electrical Resistivity 7.2e-005 ohm-cm 7.2e-005 ohm-cm at 20°C (68°F); 1.16E-04 at 650°C (1200°F) Magnetic Permeability 1.008 1.008 at RT Thermal Properties CTE, linear 20°C 17.3 µm/m-°C 9.61 µin/in-°F from from 0-100°C CTE, linear 250°C 17.8 µm/m-°C 9.89 µin/in-°F at 0-315°C (32-600°F) CTE, linear 500°C 18.7 µm/m-°C 10.4 µin/in-°F at 0-650°C Specific Heat Capacity 0.5 J/g-°C 0.12 BTU/lb-°F from 0-100°C (32-212°F) Thermal Conductivity 16.2 W/m-K 112 BTU-in/hr-ft²-°F at 0-100°C, 21.5 W/m°C at 500°C Melting Point 1400 - 1455 °C 2550 - 2650 °F Solidus 1400 °C 2550 °F Liquidus 1455 °C 2650 °F Referencesfor this datasheet. Some of the values displayed above may have been converted from their original units and/or rounded in order to display the information in a consistant format. Users requiring more precise data for scientific or engineering calculations can click on the property value to see the original value as well as raw conversions to equivalent units. We advise that you only use the original value or one of its raw conversions in your calculations to minimize rounding error. We also ask that you refer to MatWeb's disclaimer and terms of use regarding this information. MatWeb data and tools provided by MatWeb, LLC.