Journal of Thermal Analysis and Calorimetry

, Volume 111, Issue 1, pp 857–867 | Cite as

Sensor placement in temperature-based control strategies to improve baseline stability in Tian–Calvet microcalorimeters

  • Luis E. Vilchız-Bravo
  • Arturo Pacheco-VegaEmail author
  • Brent E. Handy


We address the issue of hardware placement in the development of robust temperature control strategies that can be used to maintain a stable baseline during microcalorimetric experiments. The two different control loops, each defined by the location of sensor within the calorimeter that is used to achieve control, were first developed and then tested in a fully instrumented experimental system. Both control strategies were structured on proportional-integral-derivative controllers, after which calorimetric experiments were carried out to test the efficiency and robustness of the corresponding methodology. Results indicate that sensor placement plays a fundamental role in the controlled baseline stability and that is better to place the sensing device closer to the heater than to the central core. As part of this study, comparisons were also done against a previously reported control scheme based on heat-flow measurements. Results indicate that controlling only one variable, either temperature or heat flow is sufficient to compensate for heater-induced noise, but not for external fluctuations for which a combined strategy may be necessary.


Tian–Calvet microcalorimeter Temperature control Sensor placement Baseline signal 

List of symbols


Error signal


PID controller gains


Calibration constant


Characteristic length


Electric power (W)


Heat-flow rate (W)


Temperature (K)


Temperature at T1 (K)


Temperature at T2 (K)




Input voltage signal (V)

Greek symbols


Thermal diffusivity (m2/s)


Time interval (s)


Thermal lag

Subscripts and superscripts






Heat-flow sensor


Sample heat-flow sensing cup



Continuously modulated direct-current


Conventional temperature control


Data acquisition


Direct current


Heat-flow control


Personal computer




Power modulation system


Heat-flow sensor


Sample sensing cup


Thermocouple in heat-sink unit


Thermocouple close to SHT




Single-input single-output


Solid-state relay



Luis E. Vilchiz-Bravo was the recipient of a CONACyT Scholarship from Mexico for which we are grateful. This study has been partially supported by CONACyT 35106U and PROMEP/PTC-68 from Mexico, and by NSF IIP-0724505, IIP-0844891, and HRD-0932421 from the USA. The authors specially thank D. Loren and N. D. Green (I.T.I. company) for their assistance throughout this project.


  1. 1.
    Gravelle PC. Heat-flow microcalorimetry and its application to heterogeneous catalysis. Adv Catal. 1972;22:191–263.CrossRefGoogle Scholar
  2. 2.
    Gravelle PC. Calorimetry in adsorption and heterogeneous catalysis studies. Catal Rev Sci Eng. 1977;16(1):37–110.CrossRefGoogle Scholar
  3. 3.
    Handy BE, Sharma SB, Spiewak BE, Dumesic JA. A Tian-Calvet heat-flux microcalorimeter for measurement of differential heats of adsorption. Meas Sci Technol. 1993;4:1350–56.CrossRefGoogle Scholar
  4. 4.
    Hansen LD. Calorimetric measurement of the kinetics of slow reactions. Ind Eng Chem Res. 2000;39:3541–49.CrossRefGoogle Scholar
  5. 5.
    Cardona-Martinez N, Dumesic JA. Applications of adsorption microcalorimetry to the study of heterogeneous catalysis. Adv Catal. 1992;38:149–244.CrossRefGoogle Scholar
  6. 6.
    Auroux A. Microcalorimetry methods to study the acidity and reactivity of zeolites, pillared clays and mesoporous material. Topic Catal. 2002;19:205–13.CrossRefGoogle Scholar
  7. 7.
    Hart MP, Brown DR. Surface acidities and catalytic activities of acid-activated clays. J Mol Catal A: Chem. 2004;212:315–21.CrossRefGoogle Scholar
  8. 8.
    Ostrovskii VE. Review of the heats of chemisorption of gases at metals in the context of the problem of ‘Heterogeneous’ vs. ‘Homogeneous’ catalytic surfaces. J Therm Anal Calorim. 2009;95:609–22.CrossRefGoogle Scholar
  9. 9.
    Dragoi B, Rakic V, Dumitriu E, Auroux A. Adsorption of organic pollutants over microporous solids investigated by microcalorimetry techniques. J Therm Anal Calorim. 2010;99:733–40.CrossRefGoogle Scholar
  10. 10.
    Parrillo DJ, Gorte RJ. Design parameters for the construction and operation of heat-flow calorimeters. Thermochim Acta. 1998;312:125–32.CrossRefGoogle Scholar
  11. 11.
    Hansen LD, Eatough DJ. Comparison of the detection limits of microcalorimeters. Thermochim Acta. 1983;70:257–68.CrossRefGoogle Scholar
  12. 12.
    Garcia-Cuello V, Moreno-Pirajan JC, Giraldo-Gutierrez L, Sapag K, Zgrablich G. Variation of the noise levels in the baseline of an adsorption microcalorimeter. J Therm Anal Calorim. 2009;97:705–9.CrossRefGoogle Scholar
  13. 13.
    Inaba H, Takahashi S, Mima T, Naito K. A high temperature Tian-Calvet type calorimeter and an analysis of the baseline fluctuation. J Chem Thermodyn. 1984;16:573–82.CrossRefGoogle Scholar
  14. 14.
    Ostrovskii VE. Molar heats of chemisorption of gases at metals: review of experimental results and technical problems. Thermochim Acta. 2009;489:5–21.CrossRefGoogle Scholar
  15. 15.
    Vilchiz LE, Pacheco-Vega A, Handy BE. Heat-flow patterns in Tian-Calvet microcalorimeters: conductive, convective, and radiative transport in gas dosing experiments. Thermochim Acta. 2005;439:110–8.CrossRefGoogle Scholar
  16. 16.
    Garcia-Cuello V, Moreno-Pirajan JC, Giraldo-Gutierrez L, Sapag K, Zgrablich G. Design, calibration, and testing of a new Tian-Calvet heat-flow microcalorimeter for measurement of differential heats of adsorption. Instrum Sci Technol. 2008;36:455–75.CrossRefGoogle Scholar
  17. 17.
    Hemmerich JL, Serio L, Milverton P. High-resolution tritium calorimetry based on inertial temperature control. Rev Sci Instrum. 1994;65:1616–20.CrossRefGoogle Scholar
  18. 18.
    Velazquez-Campoy A, Lopez-Mayorga O, Cabrerizo-Vilchez MA. Development of an isothermal titration microcalorimetric system with digital control and dynamic power Peltier compensation. I. Description and basic performance. Rev Sci Instrum. 2000;71:1824–31.CrossRefGoogle Scholar
  19. 19.
    Vilchiz-Bravo LE, Pacheco-Vega A, Handy BE. Heat-flow and temperature control in Tian-Calvet microcalorimeters: toward higher detection limits. Meas Sci Technol. 2010. doi: 10.1088/0957-0233/21/11/115103.
  20. 20.
    Vilchiz-Bravo LE. Heat transfer numerical simulations and control strategies to improve thermal sensitivity in Tian-Calvet calorimeters (in Spanish). PhD Thesis, Universidad Autónoma de San Luis Potosí, México. 2007.Google Scholar
  21. 21.
    Pacheco-Vega A, Ruiz-Mercado C, Peters K, Vilchiz-Bravo L. On-line fuzzy-logic-based temperature control of a concentric-tube heat exchanger facility. Heat Transf Eng. 2009;30:1208–15.CrossRefGoogle Scholar
  22. 22.
    Díaz G, Sen M, Yang KT, McClain RL. Dynamic prediction and control of heat exchangers using artificial neural networks. Int J Heat Mass Transf. 2001;44:1671–79.CrossRefGoogle Scholar
  23. 23.
    Kubrusly CS, Malebranche H. Sensors and controllers location in distributed systems—a survey. Automatica. 1985;21:117–28.CrossRefGoogle Scholar
  24. 24.
    Tarabanis KA, Allen PK, Tsai RY. A survey of sensor planning in computer vision. IEEE Trans Robotics Autom. 1995;11:86–104.CrossRefGoogle Scholar
  25. 25.
    Uciński D. Optimal sensor location for parameter estimation of distributed processes. Int J Control. 2000;73:1235–48.CrossRefGoogle Scholar
  26. 26.
    Abidi B, Aragam N, Yao Y, Abidi M. Survey and analysis of multimodal sensor planning and integration for wide area surveillance. ACM Comput Surv. 2008;41:1–36.CrossRefGoogle Scholar
  27. 27.
    Arbel A. Controllability measures and actuator placement in oscillatory systems. Int J Control. 1981;33:565–74.CrossRefGoogle Scholar
  28. 28.
    Ning HH. Optimal number and placements of piezoelectric patch actuators in structural active vibration control. Eng Comput. 2004;21:651–665.CrossRefGoogle Scholar
  29. 29.
    Franco W, Sen M, Yang KT. Optimization of control hardware placement in a thermal-hydraulic network. HVAC R Res. 2008;14:73–84.CrossRefGoogle Scholar
  30. 30.
    Worden K, Burrows AP. Optimal sensor placement for fault detection. Eng Struct. 2001;23:885–901.CrossRefGoogle Scholar
  31. 31.
    Meo M, Zumpano G. On the optimal sensor placement techniques for a bridge structure. Eng Struct. 2005;27:1488–97.CrossRefGoogle Scholar
  32. 32.
    Yao Y, Chen CH, Abidi B, Page D, Koschan A, Abidi M. Can you see me now? Sensor positioning for automated and persistent surveillance. IEEE Trans Sys Man Cyber-B. 2010;40:101–15.CrossRefGoogle Scholar
  33. 33.
    Reda S, Cochran RJ, Nowroz AN. Improved thermal tracking for processors using hard and soft sensor allocation techniques. IEEE Trans Comput. 2011;60:841–51.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2012

Authors and Affiliations

  • Luis E. Vilchız-Bravo
    • 1
  • Arturo Pacheco-Vega
    • 2
    Email author
  • Brent E. Handy
    • 3
  1. 1.Facultad de Ingeniería QuímicaUniversidad Autónoma de YucatánMéridaMéxico
  2. 2.Department of Mechanical EngineeringCalifornia State University Los AngelesLos AngelesUSA
  3. 3.CIEP-Facultad de Ciencias QuímicasUniversidad Autónoma de San Luis PotosíSan Luis PotosíMéxico

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