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Máy tính độ không đảm bảo đo

Máy tính độ không đảm bảo đo (Concentration from Weighing and Volume)

Tính uncertainty for concentration and dilution kết quả from weighing error, volume error, and related inputs directly in the browser.

Xem độ không đảm bảo chuẩn tổng hợp uc, độ không đảm bảo mở rộng U=k·uc, các thành phần đóng góp chính và đầu ra sao chép sẵn sàng cho báo cáo ở cùng một nơi.

Tính combined độ không đảm bảo chuẩn uc and độ không đảm bảo mở rộng U=k·uc
Convert tolerance notation into độ không đảm bảo chuẩn on the spot
Highlight the các thành phần đóng góp chính so you know what to improve
Chia sẻ URLs, đầu ra sao chép, and cục bộ draft saving
Template
Coverage factor k
k=2 is a common approximate 95% choice. Follow your standard or internal rule when required.

What this page covers

Combine weighing and volume uncertainty into concentration uncertainty

The công cụ combines standard uncertainties for formulas such as C=m/V, C=(m·P)/V, and C=(m·P)/(M·V).

Convert tolerance notation into độ không đảm bảo chuẩn

It handles certificate-style ±a(k=2), specification-style ±a, and triangular assumptions without making you do the conversion separately.

Visualize the dominant contributors

The contributor breakdown shows which factor dominates the variance so you can target improvements efficiently.

Sao chép đầu ra that fits reports

Switch between plain text, Markdown, CSV, and JSON and sao chép the exact format you need.

How to use

  1. Choose a template. Use concentration, dilution, ratio, or custom based on your calculation.
  2. Enter each factor value and its uncertainty. You can use either SD or tolerance notation.
  3. Choose the distribution and k value when needed.
  4. Review the kết quả, the các thành phần đóng góp chính, and the sẵn sàng cho báo cáo đầu ra sao chép before pasting it into your document.

Ví dụ

Uncertainty of mg/L from weighing and a volumetric flask

Đầu vào

m=100.00 mg ±0.10 (rectangular), V=100.00 mL ±0.08 (normal, k=2)

Đầu ra

Shows concentration, uc, U, and the contributor split between m and V.

Dilution of a standard solution

Đầu vào

C1=1000 mg/L ±5, V1=10.00 mL ±0.02, V2=100.00 mL ±0.08

Đầu ra

Shows U for the diluted concentration and which volume error matters most.

Ratios and recovery

Đầu vào

A=98.0 ±0.5, B=100.0 ±0.2

Đầu ra

Shows uncertainty for A/B or Recovery(%).

Molarity with purity and molar mass

Đầu vào

Enter m, P, M, and V together

Đầu ra

Shows the contribution from purity and molar mass as well.

Glossary

Standard uncertainty u(x)

The standard-deviation-like uncertainty associated with an đầu vào quantity x.

Combined độ không đảm bảo chuẩn uc

The độ không đảm bảo chuẩn of the kết quả y after combining all đầu vào contributions.

Expanded uncertainty U

The report-facing uncertainty calculated as U = k·uc.

Sensitivity coefficient c

A coefficient showing how strongly the kết quả changes when one đầu vào changes.

Contribution ratio

The chia sẻ of the total variance attributable to one factor.

Formulas

  • Standard uncertainty conversion: u=a/k, a/√3, a/√6
  • Combined độ không đảm bảo chuẩn: uc = √Σ(c_i·u_i)^2
  • Expanded uncertainty: U = k·uc
  • Concentration: C = m/V, (m·P)/V, (m·P)/(M·V)
  • Dilution: C2 = C1·V1/V2
  • Ratio: R = A/B

Câu hỏi thường gặp

I only have a ± value, not a standard deviation.

Tolerance notation can be converted into độ không đảm bảo chuẩn when you choose a distribution assumption. The công cụ uses u=a/k for normal(k), u=a/√3 for rectangular, and u=a/√6 for triangular.

Which k should I use?

k=2 is common, but you should follow your standard, internal rule, or customer requirement. The công cụ always shows the chosen k in the kết quả.

Can I paste this directly into a report?

Yes. Plain text, Markdown, CSV, and JSON are available, and the generated đầu ra includes assumptions, inputs, kết quả, and the top contributors.

Can I use this when inputs are correlated?

The first release assumes independent inputs. If your inputs are correlated, the kết quả can be under- or over-estimated.

Is it reliable for large errors or strongly nonlinear equations?

This công cụ uses first-order propagation. If relative uncertainties are large or the formula is strongly nonlinear, you should verify the kết quả with another method.

Notes

  • This công cụ assumes independent inputs and combines uncertainty with first-order propagation.
  • If your inputs are correlated or the formula is strongly nonlinear, the kết quả can be under- or over-estimated.
  • Automatic conversion between arbitrary concentration units is outside the first release. Enter the unit you intend to use.
  • Chia sẻ URLs include free-form labels and formulas, so do not enter confidential names.